Journal articles: 'DWT'

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Dabou, Raoult Teukam, Innocent Kamwa, Jacques Tagoudjeu, and Francis Chuma Mugombozi. "Sparse Signal Reconstruction on Fixed and Adaptive Supervised Dictionary Learning for Transient Stability Assessment." Energies 14, no. 23 (November 30, 2021): 7995. http://dx.doi.org/10.3390/en14237995.

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Fixed and adaptive supervised dictionary learning (SDL) is proposed in this paper for wide-area stability assessment. Single and hybrid fixed structures are developed based on impulse dictionary (ID), discrete Haar transform (DHT), discrete cosine transform (DCT), discrete sine transform (DST), and discrete wavelet transform (DWT) for sparse features extraction and online transient stability prediction. The fixed structures performance is compared with that obtained from transient K-singular value decomposition (TK-SVD) implemented while adding a stability status term to the optimization problem. Stable and unstable dictionary learning are designed based on datasets recorded by simulating thousands of contingencies with varying faults, load, and generator switching on the IEEE 68-bus test system. This separate supervised learning of stable and unstable scenarios allows determining root mean square error (RMSE), useful for online stability status assessment of new scenarios. With respect to the RMSE performance metric in signal reconstruction-based stability prediction, the present analysis demonstrates that [DWT], [DHT|DWT] and [DST|DHT|DCT] are better stability descriptors compared to K-SVD, [DHT], [DCT], [DCT|DWT], [DHT|DCT], [ID|DCT|DST], and [DWT|DHT|DCT] on test datasets. However, the K-SVD approach is faster to execute in both off-line training and real-time playback while yielding satisfactory accuracy in transient stability prediction (i.e., 7.5-cycles decision window after fault-clearing).

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Amhar, Fahmi, Endang Purnama Giri, Florence Elfriede Sinthauli Silalahi, Shelvie Nidya Neyman, Anggrahito, Dadan Ramdani, Danang Jaya, et al. "Ownership Protection on Digital Elevation Model (DEM) Using Transform-Based Watermarking." ISPRS International Journal of Geo-Information 11, no. 3 (March 16, 2022): 200. http://dx.doi.org/10.3390/ijgi11030200.

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This research aims to protect Digital Elevation Model (DEM) data from piracy or counterfeiting. An invisible watermark inserted into the data, which will not considerably change the data value, is necessary. The proposed method involves the use of the two-dimensional discrete cosine transform (2D DCT), a combination of 2D DCT and discrete wavelet transform (DWT), and two-dimensional discrete Fourier transform (2D DFT) in the frequency domain. The data used include a National DEM file downloaded from the geoportal of the Geospatial Information Agency (Badan Informasi Geospasial—BIG). Three files represent mountainous, lowland/urban, and coastal areas. An “attack” is also conducted on the watermarked DEM by cropping. The results indicate that the watermarked DEM is well recognized. The watermark can be read 100% for 2D DCT, while that for 2D DFT can be read 90.50%. The distortion value of the elevation data under the DCT technique demonstrates the smallest maximum value of 0.1 m compared with 4.5 and 1.1 m for 2D DFT and 2D DCT–DWT. Meanwhile, the height difference (Max Delta), the peak signal-to-noise ratio, and the root mean squared error (RMSE) are highest in mountainous, lowland, and coastal areas, respectively. Overall, the 2D DCT is also superior to the 2D DFT and the2D DCT–DWT. Although only one can recognize the nine watermarks inserted on each sheet, DEMs attacked by the cropping process can still be identified. However, this finding can sufficiently confirm that DEMs belong to BIG.

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Sujith, K. Satya. "High performance DA-based DCT, DWT and DHT." IOSR Journal of Applied Chemistry 5, no. 6 (2013): 64–70. http://dx.doi.org/10.9790/5736-0566470.

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Sujith, K. Satya. "High performance DA-based DCT, DWT and DHT." IOSR Journal of Electronics and Communication Engineering 8, no. 5 (2013): 52–58. http://dx.doi.org/10.9790/2834-0855258.

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Mousa Al-Khuzaay, Maryam I., and Waleed A. Mahmoud Al-Jawher. "New Proposed Mixed Transforms: CAW and FAW and Their Application in Medical Image Classification." International Journal of Innovative Computing 13, no. 1-2 (September 13, 2023): 15–21. http://dx.doi.org/10.11113/ijic.v13n1-2.414.

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The transformation model plays a vital role in medical image processing. This paper proposed new two Mixed Transforms models that are the hybrid combination of linear and nonlinear Transformations techniques. The first mixed transform is computed in three steps: calculate 2D discrete cosine transform (DCT) of the image, and applying Arnold Transform (AT) on the DCT coefficients, and applying the discrete Wavelet Transform (DWT) on the result to get which was abbreviated as (CAW). The second mixed transform consists of firstly computing the discrete Fourier transform (DFT), net applying the Arnold Transform (AT), and finally, the computation of discrete Wavelet Transform (DWT) which was abbreviated as (FAW). These transforms have superior directional representations as compared to other multiresolution representations such as DWT or DCT and work as non-adaptive mixed transformations for multi-scale object analysis. Due to their relationship to the wavelet idea, they are finding increasing use in areas like image processing and scientific computing. These transforms are tested in medical image classification task and their performances are compared with that of the traditional transforms. CAW and FAW transforms are used in the feature extraction stage of a classification VGG16 deep learning (DNN) task of Tumor MRI medical image. The numerical findings favor CAW and FAW over the wavelet transform for estimating and classifying pictures. From the results obtained it was shown that the CAW and FAW transform gave e much higher classification rate than that achieved with the traditional transforms, namely DCT, DFT and DWT. Furthermore, this combination leads to a family of directional and multi-transformation bases for image processing.

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Tang, Ling, Ming Ju Chen, and Hong Song. "Hybrid Color Image Compression Using Discrete Cosine Transform and Discrete Wavelet Transform." Applied Mechanics and Materials 198-199 (September 2012): 244–48. http://dx.doi.org/10.4028/www.scientific.net/amm.198-199.244.

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In this research we undertake a study of image compression based on the discrete cosine transform(DCT) and discrete wavelet transform(DWT). Then a hybrid color image compression algorithm based on DCT and DWT is proposed. This algorithm is implemented through transform the color image using DWT in the YCbCr space first, and then DCT in the low frequency, adopt huffman coding, RLE and arithmetic coding in the encoded mode. In experiments, the results outperform the only DCT and the only DWT typically higher in peak signal-to-noise ratio and have better visual quality.

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Setyono, Andik, and De Rosal Ignatius Moses Setiadi. "Image watermarking using discrete wavelet-tchebichef transform." Indonesian Journal of Electrical Engineering and Computer Science 16, no. 3 (December 1, 2019): 1416. http://dx.doi.org/10.11591/ijeecs.v16.i3.pp1416-1423.

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<span>Image watermarking is one of the most popular techniques for authenticating copyright on the digital image. Many research on image watermarking has proved that the joint of Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) combinations can improve both imperceptibility and robustness when compared to DCT or DWT only. Discrete Tchebichef Transform (DTT) denotes an alternative transformation that has a similarity property with DCT. DTT has an advantage in reducing memory requirements during computing, so the calculation speed is much faster than DCT. This study tested the performance of DTT and DCT on non-blind image watermarking method, where DTT and DCT are performed after DWT. Based on the experimental results, this research proved that the DTT was combined successfully with DWT and very potential for further investigation because it has a computing performance much better than DCT. While the image watermarking quality, both the imperceptibility and robustness aspects were completely identical with the combination of DCT and DWT transformation.</span>

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Aulia, Suci, and Arif Setiawan. "PENGENALAN TULISAN TANGAN KARAKTER HIRAGANA MENGGUNAKAN DCT, DWT, DAN K-NEAREST NEIGHBOR." Jurnal Elektro dan Telekomunikasi Terapan 4, no. 1 (October 25, 2017): 467. http://dx.doi.org/10.25124/jett.v4i1.993.

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Penelitian untuk mengenali karakter huruf hiragana berbasis image processing telah banyakdilakukan dan bahkan tingkat akurasi hampir mendekati 100%. Namun citra masukkan yangdigunakan masih berupa karakter huruf jepang hasil print-out sedangkan untuk masukkan berupatulisan tangan belum dilakukan. Maka pada penelitian ini diujikan pengenalan huruf hiragana yangberasal dari tulisan tangan berformat .jpeg. Dari beberapa strudi terkait, pendekatan kompresi yangpaling sering digunakan untuk citra JPEG adalah algoritma DCT dan DWT, sehingga keduaalgoritma tersebut digunakan pada penelitian ini untuk diujikan dan dibandingkan performansinya.Pada sistem diujikan 45 citra dari 3 orang tulisan tangan karakter hiragana dengan klasifikasiberbasis KNN dimana sebelumnya 45 citra yang berbeda dari 3 orang tersebut di training olehmasing-masing algoritma DWT dan DCT. Hasilnya berdasarkan parameter jarak yang ada padaalgoritma KNN, algoritma DWT lebih unggul dibandingkan algoritma DCT. Pencapaian tingkatakurasi maksimum diperoleh untuk masing-masing algoritma DWT-DCT adalah pada parametercityblok 82.61 % (DWT) dan correlation 58.70 % (DCT).

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Apu Hosen, Md, Shahadat Hoshen Moz, Sk Shalauddin Kabir, Md Nasim Adnan, and Syed Md. Galib. "In-depth exploration of digital image watermarking with discrete cosine transform and discrete wavelet transform." Indonesian Journal of Electrical Engineering and Computer Science 33, no. 1 (January 1, 2024): 581. http://dx.doi.org/10.11591/ijeecs.v33.i1.pp581-590.

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Digital image watermarking is a crucial technique used to protect the integrity and ownership of digital images by embedding imperceptible watermarks into the image content. This review concentrates on the utilization of discrete cosine transform (DCT) and discrete wavelet transform (DWT) in digital image watermarking schemes. DCT, widely used in image compression like JPEG, is an attractive choice for watermarking, modifying DCT coefficients with minimal impact on image quality. On the other hand, DWT offers multiresolution representation, enabling better localization and robustness against attacks. DWT-based methods use wavelet coefficients to embed watermarks in specific frequency bands or image regions. The review examines the strengths and weaknesses of DCT and DWT in digital image watermarking, exploring algorithms and approaches proposed in the literature. It also addresses challenges like attacks, synchronization, and robustness to image processing. Additionally, a comparative analysis of DCT and DWT-based methods considers imperceptibility, robustness, capacity, and computational complexity. By offering valuable insights, this review aids researchers and practitioners in implementing secure and efficient digital image watermarking solutions.

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Jang, Bong-Joo, Sanghun Lim, Won Kim, and Huiseong Noh. "DCT and DWT based Damaged Weather Radar Image Retrieval." Journal of Korea Multimedia Society 20, no. 2 (February 28, 2017): 153–62. http://dx.doi.org/10.9717/kmms.2017.20.2.153.

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Maulida, Kurnia. "Studi Komparasi Video Watermarking dengan Algoritma Discrete Wavelet Transform dan Discrete Cosine Transform." MATHunesa: Jurnal Ilmiah Matematika 8, no. 3 (November 21, 2020): 254–60. http://dx.doi.org/10.26740/mathunesa.v8n3.p254-260.

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Perkembangan teknologi di era digital berkembang dengan sangat cepat setiap harinya. Dengan perkembangan teknologi digital saat ini, media sosial dapat memudahkan kita untuk mengakses serta mendistribusikan teks, gambar, video, dan lainnya. Risiko terjadinya kejahatan di video lebih tinggi dibandingkan dengan teks dan gambar. Digital watermarking dapat digunakan untuk melindungi informasi digital dari manipulasi dan distribusi illegal. Penyisipan watermark umumnya dilakukan dalam domain spasial atau domain frekuensi. Metode yang digunakan adalah Discrete Wavelet Transform (DWT) dan Discrete Cosine Transform (DCT). DWT digunakan untuk mendapatkan komponen multi-resolusi yaitu horisontal, vertikal dan diagonal dari suatu gambar. Sedangkan, DCT memisahkan setiap blok gambar menjadi pita frekuensi rendah, sedang dan tinggi. PSNR adalah rasio antara kekuatan maksimum yang mungkin dari sinyal dan kekuatan noise yang merusak. Berdasarkan penelitian yang dilakukan penulis semakin besar koefisien DCT/DWT maka semakin bagus kualitas gambar hasil ekstrak. Hasil uji coba menunjukkan nilai PSNR video watermark menggunakan DWT lebih besar daripada nilai PSNR video watermark menggunakan DCT. Namun, selisih nilai PSNR antara DWT dan DCT sangat kecil. Nilai PSNR video watermark lebih kecil dari 30 mengindikasikan kedua video memiliki kemiripan yang rendah. Semakin besar nilai PSNR video semakin bagus kualitas video tersebut.

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Faza, Aditya Mahmud, Cepy Slamet, and Dian Nursantika. "Analisis Kinerja Kompresi Citra Digital dengan Komparasi DWT, DCT dan Hybrid (DWT-DCT)." Jurnal Online Informatika 1, no. 1 (June 1, 2016): 1. http://dx.doi.org/10.15575/join.v1i1.3.

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Sudrajat, Ari, and Ayu Hendrati Rahayu. "Watermarking using DCT and DWT on Pneumonia images." Journal of Applied Intelligent System 8, no. 3 (November 30, 2023): 273–86. http://dx.doi.org/10.33633/jais.v8i3.8914.

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Watermarking is a branch of the data hiding technique. Watermarking is a technique used to insert a copyright label on an image, so that the copyright of the image can be protected. Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) are techniques that can be used to watermark. In this study, the Discrete Cosine Transform and Discrete Wavelet Transform methods will be used to watermark images to 5 different host images. In the tests carried out, watermarking techniques will be compared using DCT, DWT, DCT-DWT combination and DWT-DCT combination. The results obtained in this study were the highest PSNR value obtained at 41.931, the highest SSIM obtained 0.99515, the highest entropy was also obtained at 7.4186, The best UACI value is 0.0071158 and the best NCPR value is obtained at 93.9068% then, for the best CC value is obtained at 0.99953. As well as the NCC value, the value obtained is the same all in each test, namely with a value of 1.

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Balsa, Jose. "Comparison of Image Compressions: Analog Transformations." Proceedings 54, no. 1 (August 21, 2020): 37. http://dx.doi.org/10.3390/proceedings2020054037.

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A comparison between the four most used transforms, the discrete Fourier transform (DFT), discrete cosine transform (DCT), the Walsh–Hadamard transform (WHT) and the Haar-wavelet transform (DWT), for the transmission of analog images, varying their compression and comparing their quality, is presented. Additionally, performance tests are done for different levels of white Gaussian additive noise.

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He, Wen Juan, Jing Liu, Yuan Yi Hu, and Jing Yi Wang. "A New Digital Watermarking Algorithm Based on DWT-DCT-RLC." Advanced Engineering Forum 1 (September 2011): 188–92. http://dx.doi.org/10.4028/www.scientific.net/aef.1.188.

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The paper presents an imperceptible and robust digital watermarking algorithm using a combination of the DWT-DCT , which improves the robustness via using new embedding strategy. Apply 4-level DWT to the host image. Then, DCT transform of each directional middle frequencies DWT subband is computed; A binary watermarked logo is coded by Run-Length Code(RLC);The watermark bits are embedded in the coefficients of the DCT block based on the energy of each corresponding to coefficient in the highest level selected using the value of RLC. Performance evaluation show that the proposed scheme is invisible and robust against common image manipulations like JPEG compression, noise adding, sharpening, filtering.

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Bazine, Razika, Huayi Wu, and Kamel Boukhechba. "Spectral DWT Multilevel Decomposition with Spatial Filtering Enhancement Preprocessing-Based Approaches for Hyperspectral Imagery Classification." Remote Sensing 11, no. 24 (December 5, 2019): 2906. http://dx.doi.org/10.3390/rs11242906.

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In this paper, spectral–spatial preprocessing using discrete wavelet transform (DWT) multilevel decomposition and spatial filtering is proposed for improving the accuracy of hyperspectral imagery classification. Specifically, spectral DWT multilevel decomposition (SDWT) is performed on the hyperspectral image to separate the approximation coefficients from the detail coefficients. For each level of decomposition, only the detail coefficients are spatially filtered instead of being discarded, as is often adopted by the wavelet-based approaches. Thus, three different spatial filters are explored, including two-dimensional DWT (2D-DWT), adaptive Wiener filter (AWF), and two-dimensional discrete cosine transform (2D-DCT). After the enhancement of the spectral information by performing the spatial filter on the detail coefficients, DWT reconstruction is carried out on both the approximation and the filtered detail coefficients. The final preprocessed image is fed into a linear support vector machine (SVM) classifier. Evaluation results on three widely used real hyperspectral datasets show that the proposed framework using spectral DWT multilevel decomposition with 2D-DCT filter (SDWT-2DCT_SVM) exhibits a significant performance and outperforms many state-of-the-art methods in terms of classification accuracy, even under the constraint of small training sample size, and execution time.

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Alex Rajju Balan, J. A., and S. Edward Rajan. "A novel embedding technique for lossless data hiding in medical images employing histogram shifting method." International Journal of Wavelets, Multiresolution and Information Processing 12, no. 03 (May 2014): 1450026. http://dx.doi.org/10.1142/s021969131450026x.

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In this paper, a lossless data hiding method based on histogram shifting for MR images using Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT) are presented. In this method, the algorithms are validated to hide the data in wavelet coefficients of high frequency subbands. This scheme has the advantage of comparing the DCT coefficients and the DWT coefficients which permit low distortion between the watermarked image and the original image. It also shifts a part of the histogram of high frequency subbands and embeds the data by using the created histogram zero point. To prevent the overflows and underflows in the spatial domain, caused by the modification of the DCT coefficients and the DWT coefficients, the histogram modification technique is applied. Therefore, we present a validated method to evaluate and compare the performance of DWT and DCT on task, in terms of data embedding payload and the Peak Signal to Noise Ratio (PSNR) in the medical image. A careful experimental analysis validates the method showing its superiority over the existing methods.

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Chen, Guang Xue, Bao Lin Tang, Qi Feng Chen, and Jing Lei Tai. "Research into Digital Watermark Algorithm Based on Wavelet Domain." Advanced Engineering Forum 6-7 (September 2012): 525–29. http://dx.doi.org/10.4028/www.scientific.net/aef.6-7.525.

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In this paper, the key research was focused on the algorithm based on wavelet domain after analyzing and comparing several watermark algorithms. Disperse Wave Transform(DWT) watermark and Disperse Cosine Transform(DCT) watermark are both belong to transform domain technology, and they have more robustness than spatial-temporal domain technology, and DWT is superior to DCT. DWT can use the spatial-frequency characteristics of Human Visual System, and Mosaic will not appear in reconstruct image. DWT also can use image fusion technology to disperse watermark into multiple scales of carrier data, and got more robustness. In this paper, watermark embedding based on wavelet domain in which raster data are carrier was performed, then extracting and detecting watermark were done. Experiment results show that digital watermark based on wavelet domain will get better invisibility and robustness, and can be used in following the data by digital fingerprint.

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Islam, Md Saiful, and Ui Pil Chong. "A Digital Image Watermarking Algorithm Based on DWT DCT and SVD." International Journal of Computer and Communication Engineering 3, no. 5 (2014): 356–60. http://dx.doi.org/10.7763/ijcce.2014.v3.349.

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Journal, Baghdad Science. "Combined DWT and DCT Image Compression Using Sliding RLE Technique." Baghdad Science Journal 8, no. 3 (September 4, 2011): 832–39. http://dx.doi.org/10.21123/bsj.8.3.832-839.

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A number of compression schemes were put forward to achieve high compression factors with high image quality at a low computational time. In this paper, a combined transform coding scheme is proposed which is based on discrete wavelet (DWT) and discrete cosine (DCT) transforms with an added new enhancement method, which is the sliding run length encoding (SRLE) technique, to further improve compression. The advantages of the wavelet and the discrete cosine transforms were utilized to encode the image. This first step involves transforming the color components of the image from RGB to YUV planes to acquire the advantage of the existing spectral correlation and consequently gaining more compression. DWT is then applied to the Y, U and V color space information giving the approximate and the detail coefficients. The detail coefficients are quantized, coded using run length encoding (RLE) and SRLE. The approximate coefficients were coded using DCT, since DCT has superior compression performance when image information has poor power concentration in high frequency areas. This output is also quantized, coded using RLE and SRLE. Test results showed that the proposed DWT DCT SRLE system proved to have encouraging results in terms of Peak Signal-to-Noise Ratio (PSNR), Compression Factor (CF) and execution time when compared with some DWT based image compressions.

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Baithoon, Nushwan Y. "Combined DWT and DCT Image Compression Using Sliding RLE Technique." Baghdad Science Journal 8, no. 3 (September 4, 2011): 832–39. http://dx.doi.org/10.21123/bsj.2011.8.3.832-839.

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A number of compression schemes were put forward to achieve high compression factors with high image quality at a low computational time. In this paper, a combined transform coding scheme is proposed which is based on discrete wavelet (DWT) and discrete cosine (DCT) transforms with an added new enhancement method, which is the sliding run length encoding (SRLE) technique, to further improve compression. The advantages of the wavelet and the discrete cosine transforms were utilized to encode the image. This first step involves transforming the color components of the image from RGB to YUV planes to acquire the advantage of the existing spectral correlation and consequently gaining more compression. DWT is then applied to the Y, U and V color space information giving the approximate and the detail coefficients. The detail coefficients are quantized, coded using run length encoding (RLE) and SRLE. The approximate coefficients were coded using DCT, since DCT has superior compression performance when image information has poor power concentration in high frequency areas. This output is also quantized, coded using RLE and SRLE. Test results showed that the proposed DWT DCT SRLE system proved to have encouraging results in terms of Peak Signal-to-Noise Ratio (PSNR), Compression Factor (CF) and execution time when compared with some DWT based image compressions.

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Takale, Swapnil, and Dr Altaaf Mulani. "DWT-PCA based Video Watermarking." Journal of Electronics,Computer Networking and Applied Mathematics, no. 26 (November 17, 2022): 1–7. http://dx.doi.org/10.55529/jecnam.26.1.7.

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Progressed watermarking video may be a methodology for embedding additional data another to video salute. Embedded data is utilized for proprietor copyright or recognizable affirmation. It added up to approach for watermarking is shown in this System, by utilizing Discrete Wavelet Alter (DWT) and Crucial Component Examination (PCA). There are a number of watermarking strategies like DCT, DWT, and DWT-SVD, but there's a downside inside the watermarking to stand up to attacks. In this way the cutting edge progressed picture watermarking calculation is proposed which provide solid watermarking with insignificant whole of bending in case of ambushes. DWT offers flexibility and PCA makes a distinction in diminishing relationship among the wavelet coefficients.

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Al-Haj, Ali. "Combined DWT-DCT Digital Image Watermarking." Journal of Computer Science 3, no. 9 (September 1, 2007): 740–46. http://dx.doi.org/10.3844/jcssp.2007.740.746.

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Wright, Ashley, Jeffrey P. Walker, David E. Robertson, and Valentijn R. N. Pauwels. "A comparison of the discrete cosine and wavelet transforms for hydrologic model input data reduction." Hydrology and Earth System Sciences 21, no. 7 (July 27, 2017): 3827–38. http://dx.doi.org/10.5194/hess-21-3827-2017.

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Abstract. The treatment of input data uncertainty in hydrologic models is of crucial importance in the analysis, diagnosis and detection of model structural errors. Data reduction techniques decrease the dimensionality of input data, thus allowing modern parameter estimation algorithms to more efficiently estimate errors associated with input uncertainty and model structure. The discrete cosine transform (DCT) and discrete wavelet transform (DWT) are used to reduce the dimensionality of observed rainfall time series for the 438 catchments in the Model Parameter Estimation Experiment (MOPEX) data set. The rainfall time signals are then reconstructed and compared to the observed hyetographs using standard simulation performance summary metrics and descriptive statistics. The results convincingly demonstrate that the DWT is superior to the DCT in preserving and characterizing the observed rainfall data records. It is recommended that the DWT be used for model input data reduction in hydrology in preference over the DCT.

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DESAI, USHA, ROSHAN JOY MARTIS, C. GURUDAS NAYAK, G. SESHIKALA, K. SARIKA, and RANJAN SHETTY K. "DECISION SUPPORT SYSTEM FOR ARRHYTHMIA BEATS USING ECG SIGNALS WITH DCT, DWT AND EMD METHODS: A COMPARATIVE STUDY." Journal of Mechanics in Medicine and Biology 16, no. 01 (February 2016): 1640012. http://dx.doi.org/10.1142/s0219519416400121.

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Electrocardiogram (ECG) signal is a non-invasive method, used to diagnose the patients with cardiac abnormalities. The subjective evaluation of interval and amplitude of ECG by physician can be tedious, time consuming, and susceptible to observer bias. ECG signals are generated due to the excitation of many cardiac myocytes and hence resultant signals are non-linear in nature. These subtle changes can be well represented and discriminated in transform and non-linear domains. In this paper, performance of Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT) and Empirical Mode Decomposition (EMD) methods are compared for automated diagnosis of five classes namely Non-ectopic (N), Supraventricular ectopic (S), Ventricular ectopic (V), Fusion (F) and Unknown (U) beats. Six different approaches: (i) Principal Components (PCs) on DCT, (ii) Independent Components (ICs) on DCT, (iii) PCs on DWT, (iv) ICs on DWT, (v) PCs on EMD and (vi) ICs on EMD are employed in this work. Clinically significant features are selected using ANOVA test ([Formula: see text]) and fed to k-Nearest Neighbor (k-NN) classifier. We have obtained a classification accuracy of 99.77% using ICs on DWT method. Consistency of performance is evaluated using Cohen’s kappa statistic. Developed approach is robust, accurate and can be employed for mass diagnosis of cardiac healthcare.

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Han, Bao Ru, Jing Bing Li, and Liang Zong. "Application of Chaotic Neural Network and 3D DWT-DFT in Medical Volume Data Watermarking." Applied Mechanics and Materials 411-414 (September 2013): 1209–12. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.1209.

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This paper proposes a digital watermarking method for the protection of medical volume data based on chaotic neural network and 3D DWT-DFT. In order to improve the security of digital watermarking, it uses chaotic sequence for scrambling .The chaotic sequence is generated by chaotic neural network. It makes full use of multi-level decomposition characteristics of 3D DWT-DFT, embedding watermark in the transform domain. The experimental results show that the method can resist filtering and rotation attacks, which has good robustness.

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Hamidi, Mohamed, Mohamed El Haziti, Hocine Cherifi, and Mohammed El Hassouni. "A Hybrid Robust Image Watermarking Method Based on DWT-DCT and SIFT for Copyright Protection." Journal of Imaging 7, no. 10 (October 19, 2021): 218. http://dx.doi.org/10.3390/jimaging7100218.

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In this paper, a robust hybrid watermarking method based on discrete wavelet transform (DWT), discrete cosine transform (DCT), and scale-invariant feature transformation (SIFT) is proposed. Indeed, it is of prime interest to develop robust feature-based image watermarking schemes to withstand both image processing attacks and geometric distortions while preserving good imperceptibility. To this end, a robust watermark is embedded in the DWT-DCT domain to withstand image processing manipulations, while SIFT is used to protect the watermark from geometric attacks. First, the watermark is embedded in the middle band of the discrete cosine transform (DCT) coefficients of the HL1 band of the discrete wavelet transform (DWT). Then, the SIFT feature points are registered to be used in the extraction process to correct the geometric transformations. Extensive experiments have been conducted to assess the effectiveness of the proposed scheme. The results demonstrate its high robustness against standard image processing attacks and geometric manipulations while preserving a high imperceptibility. Furthermore, it compares favorably with alternative methods.

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Şahin, Canberk, and Mustafa Özden. "Framework for Localization of Forgery Regions in Image." International Conference on Applied Engineering and Natural Sciences 1, no. 1 (July 22, 2023): 1071–78. http://dx.doi.org/10.59287/icaens.1131.

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With the development of computer technologies, manipulations are made on digital images without leaving a clear trace thanks to image processing software. There is a great need for applications to detect forgered images made with malicious intent in many fields such as politics, law, medicine and military. Many studies have been carried out and various algorithms have been developed to detect forgered regions by detecting forgered images. Today, superior methods are developed by combining traditional image forgery techniques with deep learning techniques. In this study, the Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) were used together with Convolutional Neural Networks (CNN) to locate the forgered regions of the forgered images. Three different methods were made to locate the forgered region. In the first method, DWT and CNN were used together. In the second method, DCT and CNN were used together. In the last method, DCT and DWT were combined in parallel and used together with CNN.

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Somasekhar, B., Ch Mohana Krishna, and Y. Murty. "Investigations on wavelet and Fourier transform based channel estimation in MIMO-OFDM system." International Journal of Engineering & Technology 7, no. 2.21 (April 20, 2018): 228. http://dx.doi.org/10.14419/ijet.v7i2.21.12178.

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In this paper channel estimation methods for MIMO-OFDM system are investigated based on Fourier Transform and Wavelet Transform. The channel estimation algorithm based on Discrete Fourier Transform (DFT) cause energy leakage in multipath channel with non-sample-spaced time delays. Discrete Cosine Transform (DCT) based channel estimator can mitigate the drawback of Discrete Fourier Transform based channel estimator, when the non-sample spaced path delays are available in multipath fading channels. Wavelet based systems provide better spectral efficiency because of no cyclic prefix requirement, with narrow side lobes and also exhibit improved BER performance. Simulation results reveal that the DWT based transform outperforms the conventional DFT and DCT based channel estimator in terms of bit error rate and mean square error.

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Taha, Dujan B., Taha Basheer Taha, and Najla Badie Al Dabagh. "A comparison between the performance of DWT and LWT in image watermarking." Bulletin of Electrical Engineering and Informatics 9, no. 3 (June 1, 2020): 1005–14. http://dx.doi.org/10.11591/eei.v9i3.1754.

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Image watermarking algorithms can be implemented using time domain or frequency domain-based algorithms. Frequency domain watermarking produces watermarks with higher robustness; hence, many attempts have been proposed in literature using different transformations as DCT, SVD, and DWT. DWT was widely used for many reasons as its spatio-temporal feature, in which the alteration of certain portion will affect only the affected portion. In this paper an experimental comparison between the traditional DWT and the second generation of wavelet which is LWT is initiated. The experimental tests evaluated the performance of both transforms in terms of image quality and watermark robustness.

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Harathi, N., V. Meenakshi, and C. H. Suneetha. "Comparison of PSNR of DCT, DWT and DTT using Telenuclear Medical Image." i-manager's Journal on Image Processing 1, no. 3 (September 15, 2014): 23–32. http://dx.doi.org/10.26634/jip.1.3.2961.

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D. K., Onebunne, Nwabueze C. A., Ekengwu B. O., and Odukwe P. C. "Improving Bit Error Rate of MIMO-OFDM System Using Discrete Wavelet Transformation." International Journal of Advanced Networking and Applications 14, no. 02 (2022): 5378–84. http://dx.doi.org/10.35444/ijana.2022.14208.

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This paper has developed a discrete wavelet transform (DWT) for multicarrier modulation in MIMO-OFDM system. The proposed system used additive Gaussian white noise (AGWN) and Rayleigh flat fading channel with respect to SNR using binary phase shift keying (BPSK). The algorithms for various scenarios of MIMO-OFDM system have been developed and simulated in MATLAB environment. The performance metric of the system was based on bit error ratio (BER) variation over values of signal to noise ratio (SNR) for different transmit and receive antennas including single input multiple output (SIMO) arrangement. The simulation results showed that the performance of DWT based MIMO-OFDM outperformed DFT based MIMO-OFDM. For the 2×1, 2×2, 2×3 MISO and MIMO systems, the DWT scheme offered reduced BER of 1.803e-05, 1.502e-05, and 1.413e-05 against 0.005847, 0.005361, and 0.005325 for the DFT scheme with respect to signal to noise ratio (SNR) at 10 dB. Generally, the results showed that using DWT scheme in OFDM for wireless communication system does not require an extra subcarrier to provide cyclic prefix function that serves as additional cost burden and reduces bandwidth.

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BELKASIM, SAEID, XIANYU HONG, and O. BASIR. "CONTENT BASED IMAGE RETRIEVAL USING DISCRETE WAVELET TRANSFORM." International Journal of Pattern Recognition and Artificial Intelligence 18, no. 01 (February 2004): 19–32. http://dx.doi.org/10.1142/s0218001404003046.

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Image retrieval plays an important role in a broad spectrum of applications. Contentbased retrieval (CBR) is one of the popular choices in many biomedical and industrial applications. Discrete image transforms have been widely studied and suggested for many image retrieval applications. The Discrete Wavelet Transform (DWT) is one of the most popular transforms recently applied to many image processing applications. The Daubechies wavelet can be used to form the basis for extracting features in retrieving images based on the description of a particular object within the scene. This wavelet is widely used for image compression. In this paper we highlight the common features between compression and retrieval. Several examples are used to test the DWT retrieval system. A comparison between DWT and Discrete Cosine Transform (DCT) is also made. The retrieval system using DWT requires preprocessing and normalization of images, which might slow down the retrieval process. The accuracy of the retrieval using DWT has been significantly improved by incorporating efficient K-Neighbor Nearest Distance (KNND) measure in our system.

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HIEN, THAI DUY, YEN-WEI CHEN, and ZENSHO NAKAO. "ROBUST DIGITAL WATERMARKING BASED ON PRINCIPAL COMPONENT ANALYSIS." International Journal of Computational Intelligence and Applications 04, no. 02 (June 2004): 183–92. http://dx.doi.org/10.1142/s1469026804001240.

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We propose a robust digital watermarking technique based on Principal Component Analysis (PCA) and evaluate the effectiveness of the method against some watermark attacks. In this proposed method, watermarks are embedded in the PCA domain and the method is closely related to DCT or DWT based frequency-domain watermarking. The orthogonal basis functions, however, are determined by data and they are adaptive to the data. The presented technique has been successfully evaluated and compared with DCT and DWT based watermarking methods. Experimental results show robust performance of the PCA based method against most prominent attacks.

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Zhang, Shun, Tie-gang Gao, and Fu-sheng Yang. "A High Capacity Reversible Data Hiding Scheme Based on Multi-Level Integer DWT and Histogram Modification." International Journal of Digital Crime and Forensics 6, no. 1 (January 2014): 51–64. http://dx.doi.org/10.4018/ijdcf.2014010104.

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A reversible data hiding scheme based on integer DWT and histogram modification is proposed. In the scheme, the cover media is firstly transformed by Integer DWT (Discrete Wavelet Transformation); then information is embedded through the modification of histograms of the middle and high frequency sub-bands of the DWT coefficients. In order to increase the embedding capacity, a multi-level scheme is proposed, which achieved both high embedding capacity and reversibility. Extensive experimental results have shown that the proposed scheme achieves both higher embedding capacity and lower distortion than spatial domain histogram modification based schemes; and it achieved better performance than integer DCT (Discrete Cosine Transformation) based histogram modification scheme.

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Mazić, Igor, Mirjana Bonković, and Anamaria Bjelopera. "The Manchester Coded Data Based OFDM (MCOFDM)." Transactions on Maritime Science 7, no. 02 (October 22, 2018): 154–63. http://dx.doi.org/10.7225/toms.v07.n02.005.

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This paper shows a new DWT based OFDM algorithm which significantly simplifies signal processing in the transmitter and receiver. Unlike conventional DWT based OFDM a new algorithm does not use digital modulation of subcarriers either IDWT in the transmitter. The output signal from the transmitter is formed by summing the signals on the individual subchannels, encoded with the Manchester code and sampled at appropriate frequencies. In the receiver, the channel signal and data is reconstructed using DWT and Haar wavelet. Although the signal transmission is achieved using amplitude modulation, the paper shows that BER performance is commensurable to BPSK or DMWT based OFDM in the presence of AWGN.

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., Neha, and Pratistha Mathur. "Three Level Optimization Models of Scaled Gabor Features for Facial Expression Recognition." International Journal of Engineering & Technology 7, no. 2.24 (April 25, 2018): 348. http://dx.doi.org/10.14419/ijet.v7i2.24.12080.

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The area of computer vision and machine learning for pattern recognition has witnessed the need for research for the development of algorithms for different applications such as human-computer interaction, automated access control and surveillance. In the field of computer vision Facial Expression Recognition has attracted the researcher’s interest. This paper presents a novel feature extraction technique: Gabor-Average-DWT-DCT for automatic facial expression recognition from a person's face image invariant of illumination. Facial Emotions have different edge and texture pattern. Gabor filter is able to extract edges and texture pattern of faces but with problem of huge dimension and high redundancy. The problem of huge dimension and high redundancy is reduced by proposed Average-DWT-DCT feature reduction technique in order to increase accuracy of system. Proposed Gabor- Average -DWT-DCT provides a compact feature vector for reducing response time of system compared to existing Gabor based expression classification. Detailed quantitative analysis is done and results that the average recognition rate of proposed technique is better than state of art results.

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Guo, Qian, Guang Xue Chen, Jian Luo, and Qi Feng Chen. "A Blind Watermarking Algorithm Using DWT and DCT Techniques for Color Image." Applied Mechanics and Materials 731 (January 2015): 179–82. http://dx.doi.org/10.4028/www.scientific.net/amm.731.179.

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In this paper, a robust watermarking technique which combines features of Discrete Wavelet Transformation (DWT) and Discrete Cosine Transformation (DCT) is proposed. Firstly the original color image is converted from RGB space to Lab space. In this technique, DWT is used to decompose the luminance coefficients into various frequency and time scale. The block DCT is applied on DWT coefficients of middle frequency to provide high level of robustness. The encrypted watermark is embedded in it by comparison of the intermediate frequency coefficients. Then the color image is converted from Lab space to RGB space to get the watermarked image. Extracting the watermark does not need the original image and the original watermark, it is a blind watermarking method. Finally, the watermarked image is attacked. Peak signal-to-noise ratio (PSNR) value and the normalized correlation (NC) coefficient value are used to evaluate this technique. Simulation experiments show that the watermark is perceptually invisible, this method can achieve the highest possible robustness without losing the transparency.

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Mohammed, Nadia. "Chaotic Image Steganography using DCT and DWT." AL-Rafidain Journal of Computer Sciences and Mathematics 10, no. 3 (September 1, 2013): 61–73. http://dx.doi.org/10.33899/csmj.2013.163536.

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Singla, Tamanna, and Ashwani Sethi. "Steganography: A Juxtaposition between LSB DCT, DWT." International Journal of Computer Applications 126, no. 11 (September 17, 2015): 6–10. http://dx.doi.org/10.5120/ijca2015906215.

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., Vasudha. "ROBUST IMAGE STEGNOGRAPHY USING DWT AND DCT." International Journal of Research in Engineering and Technology 05, no. 16 (May 25, 2016): 363–67. http://dx.doi.org/10.15623/ijret.2016.0516080.

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Lipiński, P. "On domain selection for additive, blind image watermarking." Bulletin of the Polish Academy of Sciences: Technical Sciences 60, no. 2 (October 1, 2012): 317–21. http://dx.doi.org/10.2478/v10175-012-0042-5.

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Abstract. Recently, a variety of digital watermarking schemes have been developed for copyright protection of digital images. In robust watermarking, which is used in copyright protection, transform-based algorithms are used to ensure resilience of the watermark to common signal processing attacks. The most frequently used watermarking algorithms for additive watermark embedding involve DCT, DFT, SVD and DWT domains. In this article we verify which domain is optimal for robust, the additive watermark embedding scheme. We demonstrate that in additive watermark embedding the embedding domain plays more important role than the embedding formula.

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Salau, Ayodeji Olalekan, Shruti Jain, and Joy Nnenna Eneh. "A review of various image fusion types and transforms." Indonesian Journal of Electrical Engineering and Computer Science 24, no. 3 (December 1, 2021): 1515. http://dx.doi.org/10.11591/ijeecs.v24.i3.pp1515-1522.

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Utilizing multiple views of an image is an important approach in digital photography, video editing, and medical image fusion applications. Image fusion (ImF) methods are used to improve an image's quality and remove noise from the image signal, resulting in a higher signal-to-noise ratio. A complete assessment of the literature on the different transform kinds, techniques, and rules utilized in ImF is presented in this paper. To assess the outcomes, a white flower image was fused using discrete wavelet transform (DWT) and discrete cosine transform (DCT) techniques. For validation of results, the red, green, blue (RGB) and intensity hue saturation (IHS) values of individual and fused images were evaluated. The results obtained from the fused images with the spatial IHS transform method give a remarkable performance. Furthermore, the results of the performance evaluation using DWT and DCT fusion techniques show that the same peak signal to noise ratio (PSNR) of 114.04 was achieved for both PSNR 1 and PSNR 2 for DCT, and different results were obtained for DWT. For signal to noise ratio (SNR), SNR 1 and SNR 2 achieved slightly similar values of 114.00 and 114.01 for DCT, while a SNR of 113.28 and 112.26 was achieved for SNR 1 and SNR 2 respectively.

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Li, Jingbing, Yaoli Liu, and Jiling Zhong. "3D DWT-DCT and Logistic MAP Based Robust Watermarking for Medical Volume Data." Open Biomedical Engineering Journal 8, no. 1 (December 31, 2014): 131–41. http://dx.doi.org/10.2174/1874120701408010131.

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Applying digital watermarking technique for the security protection of medical information systems is a hotspot of research in recent years. In this paper, we present a robust watermarking algorithm for medical volume data using 3D DWT-DCT and Logistic Map. After applying Logistic Map to enhance the security of watermarking, the visual feature vector of medical volume data is obtained using 3D DWT-DCT. Combining the feature vector, the third party concept and Hash function, a zero-watermarking scheme can be achieved. The proposed algorithm can mitigate the illogicality between robustness and invisibility. The experiment results show that the proposed algorithm is robust to common and geometrical attacks.

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Teng, Zi, Xiu Feng Qiu, and Jian Wei Liu. "A New Robust Color Image Watermarking Based on DWT and DRT." Applied Mechanics and Materials 278-280 (January 2013): 1366–73. http://dx.doi.org/10.4028/www.scientific.net/amm.278-280.1366.

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The copyright protection of multimedia information is more and more important in the digital age, digital watermarking is a solution to address the topic. This paper proposes a new robust image watermarking scheme based on discrete ridgelet transform (DRT) and discrete wavelet transform (DWT). The scheme respectively embeds a copy of color image watermark into DWT domain and DRT domain, and uses a conception of semi-watermark. Experiment results demonstrate that the watermark can resist various attacks such as adding Gaussian or Union Distribution Noise, JPEG compression, brightness adjustment, contrast adjustment, altering color balance, lens blur, zooming in or out, cropping and some combined attacks etc.

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Polanowski, Stanisław. "Analysis of Ratios of Propulsion Energy Demand for Transport by Bulk Carriers." Journal of KONES 26, no. 3 (September 1, 2019): 173–80. http://dx.doi.org/10.2478/kones-2019-0070.

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Abstract The article presents the results of calculations and analysis of the eM ratio of the propulsion energy consumption per the nautical mile and the eMt ratio of the propulsion energy demand for the transport of 1-ton cargo per the nautical mile for bulk carriers. The relationship between eM and eMt indicators with the EIV (Estimated Index Value) ratio is shown. The output data for the determination of eM and eMt indicators was taken from the quoted MAN publication, reading (reproducing) the values of power, velocity v and DWT tonnage from the charts included in this publication. Calculations and analyses were made for velocity v between 11-15 knots and for DWT from 5-400 kt (kilo tonnes). The graphs of eM and eMt ratios in the function of speed v and load capacity DWT are presented. Using the stepwise method of least squares, models of statistical dependence of indicators on velocity v and load capacity of bulk carriers were developed. They were based on generalized polynomials with integer exponents. Derivatives deM / dv and deMt / dv and derivatives deM / dDWT and deMt / dDWT were determined. The main observations resulting from the conducted analyses are observed with the increase of DWT (within the range of 80-100 kt) a significant decrease in the value of the eM index. For DWT values> 100 kt, the decrease in eMt is slow − eMt asymptotically tends to a constant value. The results of the analyses carried out can be used at the stage of designing the transport capacity (tonnage) and nominal speed of the ship as well as selection of ship tonnage and travel speed in a given transport situation.

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Li, Jiang, and Tsili Wang. "Efficient compression of borehole resistivity and acoustic imaging data using wavelets." GEOPHYSICS 70, no. 6 (November 1, 2005): F53—F60. http://dx.doi.org/10.1190/1.2127112.

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This paper presents a new approach to borehole resistivity and acoustic imaging data compression. The method is based on the discrete wavelet transform (DWT) combined with the set partitioning in the hierarchical trees (SPIHT) coding method. The primary advantages of the DWT + SPIHT method are its superior compression performance, simple implementation, and constant compression and transmission rate control. This new approach generally performs better than the traditional discrete cosine transform (DCT) followed by Huffman coding methods such as JPEG, particularly for target compression ratios greater than 50:1. Image block size plays a key role in using this method. To achieve the best compression performance, the image block size needs to be selected appropriately. In general, large image block sizes and more DWT decomposition levels result in higher compression ratios and/or fewer reconstruction errors. Whenever possible, image block sizes that allow the maximum levels of dyadic DWT decomposition should be used. When insufficient data samples are available in either depth or azimuthal direction, a small number of extra data samples can be added without sacrificing the overall compression performance. The DWT + SPIHT method also shows good fidelity in representing major features in borehole images such as fractures and sinusoids.

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Zhang, Zhe, Xin Bian, and Mingqi Li. "Joint Channel Estimation Algorithm Based on DFT and DWT." Applied Sciences 12, no. 15 (August 6, 2022): 7894. http://dx.doi.org/10.3390/app12157894.

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Channel estimation is an important component of orthogonal frequency division multiplexing (OFDM) systems. The existence of virtual subcarriers leads to energy spreading in the time-domain when using Inverse Fast Fourier Transform (IFFT), resulting in poor noise reduction by the conventional Discrete Fourier Transform (DFT)-based channel estimation algorithm. To tackle this problem, this paper first proposes a segmental threshold-assisted DFT-based channel estimation algorithm. The key idea is that, by utilizing the distribution characteristics of the channel and the noise components of the channel impulse response in the time-domain, different thresholds for channel estimation under different SNR conditions are set. Compared with the traditional single-threshold DFT-based algorithm, the performance of the proposed algorithm is improved. However, it still has an estimation performance floor under high SNR. Motivated by the fact that the discrete wavelet transform (DWT)-based channel estimation algorithm can achieve better estimation performance under high SNR, we propose a joint channel estimation algorithm based on DFT and DWT, which can achieve dynamic optimal selection of the two estimation methods without any prior information. Simulation results of the Wi-Fi 6 system show that the mean square error (MSE) simulation performance of the joint channel estimation algorithm is close to its theoretical approximation. It achieves the optimal estimation of MSE and BER performance across the entire SNR range compared with the separated DFT-based or DWT-based channel estimation algorithms.

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Masykuroh, Kholidiyah. "Analisis Pengaruh Koefisien Watermarking pada Citra RGB dengan Menggunakan Perbandingan DCT dan DWT." TELKA - Telekomunikasi Elektronika Komputasi dan Kontrol 7, no. 1 (May 24, 2021): 62–70. http://dx.doi.org/10.15575/telka.v7n1.62-70.

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Perkembangan internet yang semakin pesat dan kemudahan akses informasi digital menjadi peluang terjadinya cybercrime. Teknik pengamanan diperlukan pada informasi yang akan dikirimkan melalui media transmisi baik wireless maupun wired. Melalui penerapan watermarking diharapkan informasi terjaga dari serangan, penyisipan, penghapusan data, dan penggantian data. Penelitian ini membahas perbandingan metode watermarking menggunakan Discrete Cosine Transform (DCT) dan Discrete Wavelet Transform (DWT) pada citra berwarna. Means Square Error (MSE) dan Peak Signal to Noise Ratio (PSNR) merupakan parameter uji untuk mengukur rasio perbandingan citra asli dan citra watermarking. Hasil pengujian menunjukkan bahwa perbedaan jenis transformasi yang digunakan mempengaruhi nilai SNR citra RGB. Citra RGB dengan menggunakan DCT memiliki nilai SNR yang lebih tinggi dibandingkan dengan DWT yang ditunjukkan dengan nilai SNR citra Peppers 30 dB. Nilai koefisien yang diberikan pada citra yang disisipkan bervariasi mulai dari 5, 10, dan 50. Nilai ini mempengaruhi nilai SNR citra RGB dengan transformasi DCT. Along with the rapid development of the internet and the ease of access to digital information, cybercrime has a chance to occur. Security techniques are needed for information to be transmitted via transmission media, either wireless or wired. The application of watermarking has an opportunity to protect the information from attacks, insertion, deletion, and data replacement. This research discusses the comparison of watermarking methods using Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) on color images. Means Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) are a method to test parameters for measure the original image's ratio to the watermark image. The test results showed that the different types of transformations affect the SNR value of the RGB image. RGB image using DCT has a higher SNR value than DWT, which is indicated by the SNR value of Peppers image 30 dB. The coefficient value given to the inserted image varies from 5, 10, and 50. This value affects the SNR value of RGB images with DCT transformation.

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Sharma, Satender, Usha Chauhan, Ruqaiya Khanam, and Krishna Kant Singh. "Digital Watermarking using Grasshopper Optimization Algorithm." Open Computer Science 11, no. 1 (January 1, 2021): 330–36. http://dx.doi.org/10.1515/comp-2019-0023.

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Abstract The advancement in computer science technology has led to some serious concerns about the piracy and copyright of digital content. Digital watermarking technique is widely used for copyright protection and other similar applications. In this paper, a technique for digital watermarking based on Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), and Grasshopper Optimization Algorithm (GOA) is proposed. The method computes the DWT of the cover image to obtain the sub-components of the image. The subcomponent is converted to frequency domain using DCT. The challenge is to find the optimal scaling factor to be used for watermarking. The authors have designed a GOA based technique that finds the optimized scaling factor and the coefficient for embedding the watermark. GOA makes the watermark undetectable and is invisible in the cover image. The watermark image is embedded in the cover image using these coefficients. The extraction of watermark from the cover image is done by using inverse DCT and DWT. The proposed method is compared with the other state of the art methods. The effectiveness of the proposed method is computed using Peak Signal to Noise Ratio (PSNR), Normalized Cross Correlation (NCC) and Image Fidelity (IF). The proposed method outperforms the other methods and can be effectively used for practical digital watermarking.

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Journal articles on the topic 'DWT'

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