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Journal articles on the topic 'JPEG 2000'

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Published: 4 June 2021
Last updated: 25 January 2023

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1

Ono, Fumitaka. "JPEG 2000." Journal of The Institute of Image Information and Television Engineers 64, no. 9 (2010): 1339–43. http://dx.doi.org/10.3169/itej.64.1339.

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2

Ebrahimi, Touradj, Charilaos Christopoulos, and Daniel T. Lee. "JPEG 2000." Signal Processing: Image Communication 17, no. 1 (January 2002): 1–2. http://dx.doi.org/10.1016/s0923-5965(01)00031-5.

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3

Haggag, Ayman, Mohamed Ghoneim, Jianming Lu, and Takashi Yahagi. "Access Control and Scalable Encryption Using a Stream Cipher for JPEG 2000 Encoded Images." Journal of Advanced Computational Intelligence and Intelligent Informatics 11, no. 7 (September 20, 2007): 728–34. http://dx.doi.org/10.20965/jaciii.2007.p0728.

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The access control and scalable encryption scheme we propose for JPEG 2000 encoded images encrypts JEPG 2000 codestreams using the SNOW 2 progressive encryption algorithm to encrypt resolutions, quality layers, or packets independently to provide resolution, quality or fine-grain scalability. Access is controlled to different image resolutions or quality levels granted to different users receiving the same encrypted JPEG 2000 codestream but having different decryption keys. Keys used with successive resolutions or quality layers are mutually dependent based on the SHA-256 one-way hashing function. Encrypted JPEG 2000 codestreams are transcoded by an intermediate untrusted network transcoder, without decryption and without access to decryption keys. Our encryption scheme preserves most of the inherent flexibility of JPEG 2000 encoded images and is carefully designed to produce encrypted codestreams backward-compatible with JPEG 2000 compliant decoders.
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4

Emami, S. "Transmission diversity for JPEG 2000." Electronics Letters 37, no. 23 (2001): 1383. http://dx.doi.org/10.1049/el:20010939.

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5

Bernier, Richard. "An Introduction to JPEG 2000." Library Hi Tech News 23, no. 7 (August 2006): 26–27. http://dx.doi.org/10.1108/07419050610704349.

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6

Au, K. M., N. F. Law, and W. C. Siu. "Unified feature analysis in JPEG and JPEG 2000-compressed domains." Pattern Recognition 40, no. 7 (July 2007): 2049–62. http://dx.doi.org/10.1016/j.patcog.2006.11.009.

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7

OH, TICK HUI, and ROSLI BESAR. "MEDICAL IMAGE COMPRESSION USING JPEG-2000 AND JPEG: A COMPARISON STUDY." Journal of Mechanics in Medicine and Biology 02, no. 03n04 (September 2002): 313–28. http://dx.doi.org/10.1142/s021951940200054x.

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Due to the constrained bandwidth and storage capacity, medical images must be compressed before transmission and storage. However, compression will reduce image fidelity, especially when the image is compressed of lower bit rate, which cannot be tolerated in medical field. In this paper, the compression performance of the new JPEG-2000 and the more conventional JPEG is studied. The parameters used for comparison include the compression efficiency, peak signal-to-noise ratio (PSNR), picture quality scale (PQS), and mean opinion score (MOS). Three types of medical images are used — X-ray, magnetic resonance imaging (MRI) and ultrasound. Overall, the study shows that JPEG-2000 compression is more acceptable and superior compare to JPEG for lossy compression.
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8

Wei Yu, Fangting Sun, and J. E. Fritts. "Efficient rate control for JPEG-2000." IEEE Transactions on Circuits and Systems for Video Technology 16, no. 5 (May 2006): 577–89. http://dx.doi.org/10.1109/tcsvt.2006.873161.

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9

Barina, David, and Ondrej Klima. "JPEG 2000: guide for digital libraries." Digital Library Perspectives 36, no. 3 (June 4, 2020): 249–63. http://dx.doi.org/10.1108/dlp-03-2020-0014.

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Purpose The joint photographic experts group (JPEG) 2000 image compression system is being used for cultural heritage preservation. The authors are aware of over a dozen of big memory institutions worldwide using this format. This paper aims to review and explain choices for end users to help resolve trade-offs that these users are likely to encounter in practice. Design/methodology/approach The JPEG 2000 format is quite complex and therefore sometimes considered as a preservation risk. A lossy compression is governed by a number of parameters that control compression speed and rate-distortion trade-off. Their inappropriate adjustment may fairly easily lead to sub-optimal compression performance. This paper provides general guidelines for selecting the most appropriate parameters for a specific application. Findings This paper serves as a guide for the preservation of digital heritage in cultural heritage institutions, including libraries, archives and museums. Originality/value This paper serves as a guide for the preservation of digital heritage in cultural heritage institutions, including libraries, archives and museums.
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10

Lee, D. T. "JPEG 2000: Retrospective and New Developments." Proceedings of the IEEE 93, no. 1 (January 2005): 32–41. http://dx.doi.org/10.1109/jproc.2004.839613.

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11

Zhang, Chunhui, Yun Long, and Fadi Kurdahi. "A scalable embedded JPEG 2000 architecture." Journal of Systems Architecture 53, no. 8 (August 2007): 524–38. http://dx.doi.org/10.1016/j.sysarc.2006.11.010.

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12

Santa-Cruz, Diego, Raphaël Grosbois, and Touradj Ebrahimi. "JPEG 2000 performance evaluation and assessment." Signal Processing: Image Communication 17, no. 1 (January 2002): 113–30. http://dx.doi.org/10.1016/s0923-5965(01)00025-x.

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13

Taubman, David, Erik Ordentlich, Marcelo Weinberger, and Gadiel Seroussi. "Embedded block coding in JPEG 2000." Signal Processing: Image Communication 17, no. 1 (January 2002): 49–72. http://dx.doi.org/10.1016/s0923-5965(01)00028-5.

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14

Clark, Richard. "JPEG 2000 standards in digital preservation." Journal of Physics: Conference Series 231 (June 1, 2010): 012015. http://dx.doi.org/10.1088/1742-6596/231/1/012015.

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15

Marcelo, 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.

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Abstract Context.—For practitioners deploying store-and-forward telepathology systems, optimization methods such as image compression need to be studied. Objective.—To determine if Joint Photographic Expert Group (JPG or JPEG) compression, a lossy image compression algorithm, negatively affects the accuracy of diagnosis in telepathology. Design.—Double-blind, randomized, controlled trial. Setting.—University-based pathology departments. Participants.—Resident and staff pathologists at the University of Illinois, Chicago, and University of Cincinnati, Cincinnati, Ohio. Intervention.—Compression of raw images using the JPEG algorithm. Main Outcome Measures.—Image acceptability, accuracy of diagnosis, confidence level of pathologist, image quality. Results.—There was no statistically significant difference in the diagnostic accuracy between noncompressed (bit map) and compressed (JPG) images. There were also no differences in the acceptability, confidence level, and perception of image quality. Additionally, rater experience did not significantly correlate with degree of accuracy. Conclusions.—For providers practicing telepathology, JPG image compression does not negatively affect the accuracy and confidence level of diagnosis. The acceptability and quality of images were also not affected.
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16

Safdar, Muhammad, Ming Ronnier Luo, and Xiaoyu Liu. "Performance comparison of JPEG, JPEG 2000, and newly developed CSI-JPEG by adopting different color models." Color Research & Application 42, no. 4 (November 8, 2016): 460–73. http://dx.doi.org/10.1002/col.22100.

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17

Zabala, Alaitz, Raffaele Vitulli, and Xavier Pons. "Impact of CCSDS-IDC and JPEG 2000 Compression on Image Quality and Classification." Journal of Electrical and Computer Engineering 2012 (2012): 1–13. http://dx.doi.org/10.1155/2012/761067.

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This study measures the impact of both on-board and user-side lossy image compression (CCSDS-IDC and JPEG 2000) on image quality and classification. The Sentinel-2 Image Performance Simulator was modified to include these compression algorithms in order to produce Sentinel-2 simulated images with on-board lossy compression. A multitemporal set of Landsat images was used for the user-side compression scenario in order to study a crop area. The performance of several compressors was evaluated by computing the Signal-to-Noise Ratio (SNR) of the compressed images. The overall accuracy of land-cover classifications of these images was also evaluated. The results show that on-board CCSDS performs better than JPEG 2000 in terms of compression fidelity, especially at lower compression ratios (from CR 2:1 up to CR 4:1, i.e., 8 to 4 bpppb). The effect of compression on land cover classification follows the same trends, but compression fidelity may not be enough to assess the impact of compression on end-user applications. If compression is applied by end-users, the results show that 3D-JPEG 2000 obtains higher compression fidelity than CCSDS and JPEG 2000 with other parameterizations. This is due to the high dynamic range of the images (representing reflectances*10000), which JPEG 2000 is able to exploit better.
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18

Suhail, M. "A comparative study of digital watermarking in JPEG and JPEG 2000 environments." Information Sciences 151 (May 2003): 93–105. http://dx.doi.org/10.1016/s0020-0255(02)00291-8.

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19

Pinheiro, Antonio. "JPEG column: 82nd JPEG meeting in Lisbon, Portugal." ACM SIGMultimedia Records 11, no. 1 (March 2019): 1. http://dx.doi.org/10.1145/3458462.3458468.

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JPEG has been the most common representation format of digital images for more than 25 years. Other image representation formats have been standardised by JPEG committee like JPEG 2000 or more recently JPEG XS. Furthermore, JPEG has been extended with new functionalities like HDR or alpha plane coding with the JPEG XT standard, and more recently with a reference software. Another solutions have been also proposed by different players with limited success. The JPEG committee decided it is the time to create a new working item, named JPEG XL, that aims to develop an image coding standard with increased quality and flexibility combined with a better compression efficiency. The evaluation of the call for proposals responses had already confirmed the industry interest, and development of core experiments has now begun. Several functionalities will be considered, like support for lossless transcoding of images represented with JPEG standard.
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20

KULKARNI, SHIVALI D., AMEYA K. NAIK, and NITIN S. NAGORI. "2D IMAGE TRANSMISSION USING BANDWIDTH EFFICIENT MAPPING TECHNIQUE." International Journal of Image and Graphics 10, no. 04 (October 2010): 559–73. http://dx.doi.org/10.1142/s0219467810003883.

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Transmitting images over the wireless channel require that optimum compression ratio be maintained along with good image quality. This becomes a critical issue especially at higher values of bit error rate (BER). Joint photographic experts group (JPEG) standard and its successor JPEG 2000 provide excellent compression ratio but image reconstruction becomes highly difficult under extreme noise conditions. We present a mapping technique which gives better compression as compared to the existing techniques. Also, its performance is excellent even for higher bit error rates (BERs). This is supported by the results presented for JPEG, JPEG 2000, as well as mapping technique under fading channel conditions. Moreover, it is observed that the presence of high levels of noise has negligible effect on the reconstruction of images encoded using mapping technique.
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21

Smith, Michael D., and John Villasenor. "JPEG-2000 Rate Control for Digital Cinema." SMPTE Motion Imaging Journal 115, no. 10 (October 2006): 394–99. http://dx.doi.org/10.5594/j15132.

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22

van Rooy, Jan, Joost UijtdeHaag, and John Hommel. "JPEG-2000—Not Only for Digital Cinema?" SMPTE Motion Imaging Journal 115, no. 10 (October 2006): 400–405. http://dx.doi.org/10.5594/j15133.

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23

Skodras, A., C. Christopoulos, and T. Ebrahimi. "The JPEG 2000 still image compression standard." IEEE Signal Processing Magazine 18, no. 5 (2001): 36–58. http://dx.doi.org/10.1109/79.952804.

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24

Zargari, F., and O. Fatemi. "Novel error concealment methods in JPEG 2000." Canadian Journal of Electrical and Computer Engineering 30, no. 2 (2005): 73–80. http://dx.doi.org/10.1109/cjece.2005.1541728.

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25

Nein-Hsien Lin, Ting-Hao Huang, and Bing-Yu Chen. "3D Model Streaming Based on JPEG 2000." IEEE Transactions on Consumer Electronics 53, no. 1 (February 2007): 182–90. http://dx.doi.org/10.1109/tce.2007.339523.

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26

Gangadhar, Manjunath, and Dinesh Bhatia. "FPGA based EBCOT architecture for JPEG 2000." Microprocessors and Microsystems 29, no. 8-9 (November 2005): 363–73. http://dx.doi.org/10.1016/j.micpro.2004.10.006.

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27

Askelöf, Joel, Mathias Larsson Carlander, and Charilaos Christopoulos. "Region of interest coding in JPEG 2000." Signal Processing: Image Communication 17, no. 1 (January 2002): 105–11. http://dx.doi.org/10.1016/s0923-5965(01)00026-1.

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28

Marcellin, Michael W., Margaret A. Lepley, Ali Bilgin, Thomas J. Flohr, Troy T. Chinen, and James H. Kasner. "An overview of quantization in JPEG 2000." Signal Processing: Image Communication 17, no. 1 (January 2002): 73–84. http://dx.doi.org/10.1016/s0923-5965(01)00027-3.

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29

Fan, Yu-Cheng, Arvin Chiang, and Jan-Hung Shen. "ROI-based Watermarking Scheme for JPEG 2000." Circuits, Systems & Signal Processing 27, no. 5 (September 3, 2008): 763–74. http://dx.doi.org/10.1007/s00034-008-9055-6.

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30

Stolitzka, Dale, Walt Husak, and Siegfried Foessel. "New JPEG 2000 Profiles for Broadcast Contribution." SMPTE Motion Imaging Journal 120, no. 3 (April 2011): 36–44. http://dx.doi.org/10.5594/j18029.

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31

Schöberl, M., V. Bruns, S. Fößel, H. Bloss, and A. Kaup. "Change detection in JPEG 2000 compressed video." Electronics Letters 46, no. 6 (2010): 409. http://dx.doi.org/10.1049/el.2010.2945.

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32

Chang, Y. W., H. C. Fang, C. C. Cheng, C. C. Chen, and L. G. Chen. "Precompression Quality-Control Algorithm for JPEG 2000." IEEE Transactions on Image Processing 15, no. 11 (November 2006): 3279–93. http://dx.doi.org/10.1109/tip.2006.882013.

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33

Fan, Yu Cheng, and Hen Wai Tsao. "A dual pyramid watermarking for JPEG-2000." International Journal of High Performance Computing and Networking 5, no. 1/2 (2007): 84. http://dx.doi.org/10.1504/ijhpcn.2007.015767.

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34

Fiorucci, Federico, Giuseppe Baruffa, and Fabrizio Frescura. "Objective and subjective quality assessment between JPEG XR with overlap and JPEG 2000." Journal of Visual Communication and Image Representation 23, no. 6 (August 2012): 835–44. http://dx.doi.org/10.1016/j.jvcir.2012.04.011.

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35

Punchihewa, Amal. "Artefact Characterisation for JPEG and JPEG 2000 Image Codecs: Edge Blur and Ringing." Engineer: Journal of the Institution of Engineers, Sri Lanka 40, no. 3 (July 26, 2007): 25. http://dx.doi.org/10.4038/engineer.v40i3.7143.

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36

De Neve, Wesley, Davy Van Deursen, Wim Van Lancker, Yong Man Ro, and Rik Van de Walle. "Improved BSDL-based content adaptation for JPEG 2000 and HD Photo (JPEG XR)." Signal Processing: Image Communication 24, no. 6 (July 2009): 452–67. http://dx.doi.org/10.1016/j.image.2009.02.013.

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37

Brahimi, Tahar, Fouad Khelifi, and Abdellah Kacha. "An efficient JPEG-2000 based multimodal compression scheme." Multimedia Tools and Applications 80, no. 14 (March 15, 2021): 21241–60. http://dx.doi.org/10.1007/s11042-021-10776-5.

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38

Fedoseev, V., and T. Androsova. "Watermarking algorithms for JPEG 2000 lossy compressed images." Information Technology and Nanotechnology, no. 2391 (2019): 366–70. http://dx.doi.org/10.18287/1613-0073-2019-2391-366-370.

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In the paper, we propose two watermarking algorithms for semi-fragile data hiding in JPEG 2000 lossy compressed images. Both algorithms are based on the concept of quantization index modulation. These methods have a property of semi-fragility to the image quality. It means that the hidden information is preserved after high-quality compression, and is destroyed in the case of significant degradation. Experimental investigations confirm this property for both algorithms. They also show that the introduced embedding distortions in terms of PSNR and PSNR-HVS are in almost linear dependence on the quantization parameter. It allows us to control the quality at an acceptable level when information embedding
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39

Hung-Chi Fang, Yu-, Tu-Chih Wang, Chung-Jr Lian, and Liang-Gee Chen. "Parallel embedded block coding architecture for JPEG 2000." IEEE Transactions on Circuits and Systems for Video Technology 15, no. 9 (September 2005): 1086–97. http://dx.doi.org/10.1109/tcsvt.2005.852618.

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40

Chen, O. T. C., and Chih-Chang Chen. "Automatically-Determined Region of Interest in JPEG 2000." IEEE Transactions on Multimedia 9, no. 7 (November 2007): 1333–45. http://dx.doi.org/10.1109/tmm.2007.906572.

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41

Oh, Han, Ali Bilgin, and Michael Marcellin. "Visually Lossless JPEG 2000 for Remote Image Browsing." Information 7, no. 3 (July 15, 2016): 45. http://dx.doi.org/10.3390/info7030045.

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42

Cornelis, Jan G., Jan Lemeire, Tim Bruylants, and Peter Schelkens. "Heterogeneous acceleration of volumetric JPEG 2000 using OpenCL." International Journal of High Performance Computing Applications 31, no. 3 (May 10, 2016): 229–45. http://dx.doi.org/10.1177/1094342016646438.

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43

TONOMURA, Y., T. NAKACHI, and T. FUJII. "Distributed Video Coding Using JPEG 2000 Coding Scheme." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E90-A, no. 3 (March 1, 2007): 581–89. http://dx.doi.org/10.1093/ietfec/e90-a.3.581.

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44

HASHIMOTO, M. "JPEG 2000 Encoding Method for Reducing Tiling Artifacts." IEICE Transactions on Information and Systems E88-D, no. 12 (December 1, 2005): 2839–48. http://dx.doi.org/10.1093/ietisy/e88-d.12.2839.

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45

Jóźków, Grzegorz. "Terrestrial Laser Scanning Data Compression Using JPEG-2000." PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science 85, no. 5 (September 26, 2017): 293–305. http://dx.doi.org/10.1007/s41064-017-0027-y.

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46

Nguyen, Anthony, Vinod Chandran, and Sridha Sridharan. "Importance prioritisation in JPEG 2000 for improved interpretability." Signal Processing: Image Communication 19, no. 10 (November 2004): 1005–28. http://dx.doi.org/10.1016/j.image.2004.08.005.

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47

Gao, Yiming, and Xiaoping Yang. "A Cartoon-Texture Approach for JPEG/JPEG 2000 Decompression Based on TGV and Shearlet Transform." IEEE Transactions on Image Processing 28, no. 3 (March 2019): 1356–65. http://dx.doi.org/10.1109/tip.2018.2877485.

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48

Chang, Jong-Kwon. "A SoC design and implementation for JPEG 2000 Floating Point Filter." KIPS Transactions:PartA 13A, no. 3 (June 1, 2006): 185–90. http://dx.doi.org/10.3745/kipsta.2006.13a.3.185.

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49

Kouadio, Adi. "JPEG 2000: A Potential Solution for Archiving HDTV Content." SMPTE Motion Imaging Journal 118, no. 8 (November 2009): 33–40. http://dx.doi.org/10.5594/j14888.

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50

Rahman Hasso, Maha, and Sahlah Ali. "Applying Standard JPEG 2000 Part One on Image Compression." AL-Rafidain Journal of Computer Sciences and Mathematics 14, no. 1 (June 15, 2020): 13–33. http://dx.doi.org/10.33899/csmj.2020.164796.

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