Academic literature on the topic 'Image compression level'
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Journal articles on the topic "Image compression level"
Celik, Mehmet Utku, Gaurav Sharma, and A. Murat Tekalp. "Gray-level-embedded lossless image compression." Signal Processing: Image Communication 18, no. 6 (July 2003): 443–54. http://dx.doi.org/10.1016/s0923-5965(03)00023-7.
Full textDi Martino, Ferdinando, and Salvatore Sessa. "Multi-level fuzzy transforms image compression." Journal of Ambient Intelligence and Humanized Computing 10, no. 7 (August 17, 2018): 2745–56. http://dx.doi.org/10.1007/s12652-018-0971-4.
Full textCahya Dewi, Dewa Ayu Indah, and I. Made Oka Widyantara. "Usage analysis of SVD, DWT and JPEG compression methods for image compression." Jurnal Ilmu Komputer 14, no. 2 (September 30, 2021): 99. http://dx.doi.org/10.24843/jik.2021.v14.i02.p04.
Full textMarcelo, Alvin, Paul Fontelo, Miguel Farolan, and Hernani Cualing. "Effect of Image Compression on Telepathology." Archives of Pathology & Laboratory Medicine 124, no. 11 (November 1, 2000): 1653–56. http://dx.doi.org/10.5858/2000-124-1653-eoicot.
Full textGollu, Vimala Kumari, Ganta Usha Sravani, Mandru Sunil Prakash, and Ganta Srikanth. "Pipeline of Optimization Techniques for Multi-Level Thresholding in Medical Image Compression Using 2D Histogram." Traitement du Signal 38, no. 4 (August 31, 2021): 993–1006. http://dx.doi.org/10.18280/ts.380409.
Full textMoëll, Mattias K., and Minoru Fujita. "FOURIER TRANSFORM METHODS IN IMAGE ANALYSIS OF COMPRESSION WOOD AT THE CELLULAR LEVEL." IAWA Journal 25, no. 3 (2004): 311–24. http://dx.doi.org/10.1163/22941932-90000368.
Full textBarrios, Yubal, Alfonso Rodríguez, Antonio Sánchez, Arturo Pérez, Sebastián López, Andrés Otero, Eduardo de la Torre, and Roberto Sarmiento. "Lossy Hyperspectral Image Compression on a Reconfigurable and Fault-Tolerant FPGA-Based Adaptive Computing Platform." Electronics 9, no. 10 (September 26, 2020): 1576. http://dx.doi.org/10.3390/electronics9101576.
Full textSinghKatre, Surjeet. "Image Compression based on 4 Level AMBTC." International Journal of Computer Applications 95, no. 4 (June 18, 2014): 7–9. http://dx.doi.org/10.5120/16580-6275.
Full textSayed, Mohamed H., and Talaat M. Wahby. "Multi-Level Image Steganography Using Compression Techniques." International Journal of Computer Applications Technology and Research 6, no. 11 (November 4, 2017): 441–50. http://dx.doi.org/10.7753/ijcatr0611.1001.
Full textLi Donghui, 李东晖. "Context-Based Bi-Level Speckle Image Compression." Laser & Optoelectronics Progress 55, no. 12 (2018): 121010. http://dx.doi.org/10.3788/lop55.121010.
Full textDissertations / Theses on the topic "Image compression level"
Bejile, Brian. "Bi-level lossless compression techniques." Diss., Connect to the thesis, 2004. http://hdl.handle.net/10066/1481.
Full textGuo, Jianghong. "Analysis and Design of Lossless Bi-level Image Coding Systems." Thesis, University of Waterloo, 2000. http://hdl.handle.net/10012/845.
Full textКурлан, О. О., and С. В. Омельченко. "Аналіз методів компресії зображень формату JPEG для підвищення рівня стиснення." Thesis, ХНУРЕ, 2021. https://openarchive.nure.ua/handle/document/16486.
Full textTrisiripisal, Phichet. "Image Approximation using Triangulation." Thesis, Virginia Tech, 2003. http://hdl.handle.net/10919/33337.
Full textMaster of Science
Husberg, Björn. "A Portable DARC Fax Service." Thesis, Linköping University, Department of Electrical Engineering, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1373.
Full textDARC is a technique for data broadcasting over the FM radio network. Sectra Wireless Technologies AB has developed a handheld DARC receiver known as the Sectra CitySurfer. The CitySurfer is equipped with a high-resolution display along with buttons and a joystick that allows the user to view and navigate through various types of information received over DARC.
Sectra Wireless Technologies AB has, among other services, also developed a paging system that enables personal message transmission over DARC. The background of this thesis is a wish to be able to send fax documents using the paging system and to be able to view received fax documents in the CitySurfer.
The presented solution is a central PC-based fax server. The fax server is responsible for receiving standard fax transmissions and converting the fax documents before redirecting them to the right receiver in the DARC network. The topics discussed in this thesis are fax document routing, fax document conversion and fax server system design.
Grah, Joana Sarah. "Mathematical imaging tools in cancer research : from mitosis analysis to sparse regularisation." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/273243.
Full textTseng, Chi-Hung, and 曾吉宏. "A VQ-Based Image Compression for Grey-Level Image Sequences." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/29017028723748615469.
Full text大葉大學
資訊工程學系碩士班
93
Abstract A number of methods have been proposed for the compression of continuous image sequences. However, they only deal with binary images, which greatly limit their popularity in applications. In this thesis, we proposed a VQ-based method for compressing continuous grey-level images which have great similarity between two adjacent images. Four sets of continuous image sequences, each consists of 9 images with image size of 256x256 pixels, were used for testing the performance of the proposed method. Each image was first segmented into a number of 3x3 or 4x4 blocks, and then LBG algorithm was used for training a set of codebook consisting of 512 codewords capable of delineating features of the continuous image sequence. For further increasing the compression performance, JPEG-LS algorithm was applied to compress the codebook and index images of the sequential images. The results show that the compression ratio achieved by using the proposed method is significantly higher than AVI, while the image quality of the reconstructed images has been hold at a satisfied level. Future works will expand the method to application of lossless compression in medical image sequences. Keywords - Vector quantization, continuous image, image compression, AVI.
Ho, Yu-An, and 何玉安. "A Study on Bi-Level Image Data Hiding and Image Compression." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/69085995316289719990.
Full text國立中興大學
資訊科學與工程學系所
97
Data hiding, as the term itself suggests, means the hiding of secret data in a cover image, and the result is a so-called stego-image. Reversible data hiding is a kind of data hiding technique where not only the secret data can be extracted from the stego-image but the cover image can be completely rebuilt after the extraction of the secret data. Therefore, reversible data hiding is the choice in cases of secret data hiding where the recovery of the cover image is required. In this dissertation, we propose a high-capacity reversible data hiding scheme based on pattern substitution (PS). It gathers statistical data about the occurrence frequencies of different patterns and quantifies how the frequency of occurrence differs from pattern to pattern. This way, on top of the pattern occurrence frequency information, some pattern exchange relationships can be established, and PS can thus be used to do the data hiding. Then, in the extraction stage, we can reverse these patterns to their original forms and rebuild an undistorted cover image. Binary image is one of the commonly used image formats, such as FAX and document images. This dissertation proposes a binary image compression method, called QLS compression method, which uses BFT linear quadtree and logic-spectra techniques to losslessly compress a binary image. This method employs a breadth first traversal linear quadtree to divide the image into blocks, and then uses logic functions and spectral techniques to encode the blocks. This dissertation also presents a QLS hiding-compression method to encode the cover image and embed the secret data in the cover image during the encoding of the cover image. The stego-image created by the QLS hiding-compression method is quite similar to the cover image. Halftone image is commonly used by low memory space devices such as printers, fax machines, cell phones, etc. In this dissertation, a novel reversible data hiding scheme for halftone images is represented. After rendering the multi-tone image into a halftone image by error diffusion, the proposed scheme classifies blocks according to pixel permutation in the halftone image and then generates two patterns to hide secret data. The new scheme not only can securely conceal secret information, but it also can fully recover the original halftone image after the extraction of the secret information.
Wang, Her-Fa, and 王和發. "A Refined VQ Gray-Level Image Compression Method and A Low Lossy Color Image Compression Method." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/58533890694910759475.
Full text朝陽科技大學
資訊管理系碩士班
92
This paper proposes two image compression methods. The first one is called A Refined VQ Gray-level image compression method which modifies the traditional VQ-based image compression method for encoding a gray-level image. It further lossless encodes the compression data which are generated by the traditional VQ-based image compression method. Although the PSNRs of the images decompressed by the proposed method and the traditional VQ-based image compression method are the same, the a refined VQ gray-level image compression method is more efficient in memory storage. The second method integrates the techniques of quadtree, standard deviation, and quadratic regression equation to compress a color image. Let f be a YIQ-formatted color image. This method employs a set of quadratic regression equations to portray the relationships between the color components Y and I, as well as Y and Q of the pixels in f. Then, it only marks down the coefficients of the quadratic regression equations and the Y component values of all the pixels in f so as to reduce the memory space required to hold f. Generally speaking, when the decompressed image is required for a high quality, this proposed method is better, compared with the JPEG method. Moreover, the proposed method usually provides a better performance for compressing an image with slighter variation among the colors of adjacent pixels too. The blocking and Gibbs effects occurring on the image decoded by the proposed method are much less than those appearing on the image decoompressed by JPEG method.
Xia, Wen Nan, and 夏文南. "Image compression with classified interpolative multi-level block truncation coding." Thesis, 1995. http://ndltd.ncl.edu.tw/handle/25322635484554056715.
Full textBooks on the topic "Image compression level"
Toivanen, Pekka. New distance transforms for gray-level image compression. Lappeenranta, Finland: Lappeenranta University of Technology, 1996.
Find full textBook chapters on the topic "Image compression level"
Froment, Jacques. "Image Compression Through Level Lines and Wavelet Packets." In Computational Imaging and Vision, 305–39. Dordrecht: Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-015-9715-9_11.
Full textNandi, Utpal, Biswajit Laya, Anudyuti Ghorai, and Moirangthem Marjit Singh. "Three-Level Hierarchical Classification Scheme: Its Application to Fractal Image Compression Technique." In Advances in Intelligent Systems and Computing, 123–32. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5679-1_12.
Full textNobuhara, Hajime, Eduardo Masato Iyoda, Kaoru Hirota, and Witold Pedrycz. "Optimization of Image Compression Method Based on Fuzzy Relational Equations by Overlap Level of Fuzzy Sets." In Computational Intelligence for Modelling and Prediction, 163–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/10966518_12.
Full textBaraskar, Trupti, and Vijay R. Mankar. "True Color Image Compression and Decompression Using Fusion of Three-Level Discrete Wavelet Transform—Discrete Cosine Transforms and Arithmetic Coding Technique." In Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB), 469–81. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-00665-5_47.
Full textGarcía-Ordás, Diego, Laura Fernández-Robles, Enrique Alegre, María Teresa García-Ordás, and Oscar García-Olalla. "Automatic Tampering Detection in Spliced Images with Different Compression Levels." In Pattern Recognition and Image Analysis, 416–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38628-2_49.
Full textChaudhary, Ankit, and Sandeep Kumar. "Utilizing Image Color Channels for High Payload Embedding." In Handbook of Research on Emerging Perspectives in Intelligent Pattern Recognition, Analysis, and Image Processing, 116–26. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-8654-0.ch006.
Full textTsai, Chwei-Shyong, and Chin-Chen Chang. "Embedding Robust Gray-Level Watermark in an Image Using Discrete Cosine Transformation." In Distributed Multimedia Databases, 206–23. IGI Global, 2002. http://dx.doi.org/10.4018/978-1-930708-29-7.ch013.
Full textGeetha, P. "Survey of Medical Image Compression Techniques and Comparative Analysis." In Research Developments in Computer Vision and Image Processing, 327–56. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-4558-5.ch016.
Full textGeetha, P. "Survey of Medical Image Compression Techniques and Comparative Analysis." In Medical Imaging, 1165–98. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-0571-6.ch048.
Full textBassou, Abdesselam. "The Discrete Quincunx Wavelet Packet Transform." In Wavelet Theory [Working Title]. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.94970.
Full textConference papers on the topic "Image compression level"
Nguyen-Phi, K., and H. Weinrichter. "Bi-level image compression using adaptive tree model." In Proceedings DCC '97. Data Compression Conference. IEEE, 1997. http://dx.doi.org/10.1109/dcc.1997.582122.
Full textZhu, Chunbiao, Yuanqi Chen, Yiwei Zhang, Shan Liu, and Ge Li. "ResGAN: A Low-Level Image Processing Network to Restore Original Quality of JPEG Compressed Images." In 2019 Data Compression Conference (DCC). IEEE, 2019. http://dx.doi.org/10.1109/dcc.2019.00128.
Full textVeisi, Hadi, and Mansour Jamzad. "Image Compression with Neural Networks Using Complexity Level of Images." In 2007 5th International Symposium on Image and Signal Processing and Analysis. IEEE, 2007. http://dx.doi.org/10.1109/ispa.2007.4383706.
Full textRaguram, Rahul, Michael W. Marcellin, and Ali Bilgin. "Improved Resolution Scalability for Bi-Level Image Data in JPEG2000." In 2007 Data Compression Conference (DCC'07). IEEE, 2007. http://dx.doi.org/10.1109/dcc.2007.48.
Full textLe Moan, Steven, Marius Pedersen, and Aladine Chetouani. "High-Level Visual Masking of Image Compression Artefacts." In 2020 IEEE International Conference on Image Processing (ICIP). IEEE, 2020. http://dx.doi.org/10.1109/icip40778.2020.9190877.
Full textZhong, Zhisheng, Hiroaki Akutsu, and Kiyoharu Aizawa. "Channel-Level Variable Quantization Network for Deep Image Compression." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/65.
Full textAi, Wei-hua, Yun-xian Huang, Xiang Li, and Chao-ling Shen. "Lossless and lossy compression for MODIS level 0 data." In Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, edited by Jayaram K. Udupa, Nong Sang, Laszlo G. Nyul, and Hengqing Tong. SPIE, 2009. http://dx.doi.org/10.1117/12.834021.
Full textWen Sun, Yan Lu, Feng Wu, and Shipeng Li. "Level embedded medical image compression based on value of interest." In 2009 16th IEEE International Conference on Image Processing ICIP 2009. IEEE, 2009. http://dx.doi.org/10.1109/icip.2009.5414553.
Full textAnil, D., K. V. Karthik, and K. Sudhir Kumar. "A modified three level Block Truncation Coding for image compression." In 2011 International Conference on Pattern Analysis and Intelligent Robotics (ICPAIR). IEEE, 2011. http://dx.doi.org/10.1109/icpair.2011.5976907.
Full textPrasad, Venkata Rama, Vaddella, Ramesh Babu, and Inampudi. "Adaptive Gray Level Difference to Speed Up Fractal Image Compression." In 007 International Conference on Signal Processing, Communications and Networking. IEEE, 2007. http://dx.doi.org/10.1109/icscn.2007.350741.
Full textReports on the topic "Image compression level"
Libert, John M., Shahram Orandi, Michael D. Garris, and John D. Grantham. Effects of Decomposition Levels and Quality Layers with JPEG 2000 Compression of 1000 ppi Fingerprint Images. National Institute of Standards and Technology, August 2013. http://dx.doi.org/10.6028/nist.ir.7939.
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