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Journal articles on the topic 'JPEG2000'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

BALSTER, ERIC J., BENJAMIN T. FORTENER, and WILLIAM F. TURRI. "POST-COMPRESSION RATE-DISTORTION DEVELOPMENT FOR EMBEDDED BLOCK CODING WITH OPTIMAL TRUNCATION IN JPEG2000 IMAGERY." International Journal of Image and Graphics 11, no. 04 (2011): 611–27. http://dx.doi.org/10.1142/s0219467811004238.

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This paper presents a development of the post-compression rate-distortion optimization (PCRD-opt) algorithm in JPEG2000 used for optimal truncation (OT) rate control. The proposed treatment of PCRD-opt differs from the treatment given in the JPEG2000 standard and what is given in a number of publications. The proposed algorithm is implemented in a complete JPEG2000 compression engine as well as the algorithm published in the JPEG2000 standard. The proposed algorithm gives a substantial performance gain, outperforming the implementation given in the standard by 0.25–1 dB in PSNR on average, dem

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2

Ren, Ke Qiang, and Hai Ying Jiang. "Application Research of Kakadu System Based on JPEG2000." Advanced Materials Research 403-408 (November 2011): 1933–36. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.1933.

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JPEG2000 is a new compressed standard of static image, Kakadu is a open source system which can be higher efficiency to realize the algorithm of JPEG2000. This article introduces the codec construction and the compressed stream structure in JPEG2000, analyzes the construction of Kakadu and image compression class in Kakadu, and then carries on application experiments based on JPEG2000 in Kakadu 2.2 platform. Experiments show that the compression of interest image region has higher transfer rate and lower memory compared with the original image, and JPEG2000 has higher compression rate and bett

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3

OU, CHIEN-MIN, HUI-YA LI, WEN-JYI HWANG, and MEI-HWA LIU. "LAYERED IMAGE TRANSMISSION WITH QUALITY PRE-SPECIFIABLE JPEG2000." International Journal of Image and Graphics 08, no. 04 (2008): 629–41. http://dx.doi.org/10.1142/s0219467808003271.

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A novel JPEG2000-based algorithm, termed quality pre-specifiable layered JPEG2000 (QPSL-JPEG2000), for realizing a layered image transmission (LIT) system is presented in this paper. In the QPSL-JPEG2000 algorithm, the resolution and rate associated with each layer of the LIT system can be pre-specified. It encodes an image one layer at a time using the modified JPEG2000 technique. The encoding process at each layer only covers the subbands having resolution level lower than the designated resolution at that layer subject to the pre-specified incremental rate budget. The encoding results at th

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4

TSAI, TSUNG-HAN, and LIAN-TSUNG TSAI. "AN EFFICIENT DESIGN FOR MOTION-JPEG2000 SYSTEM IN REAL-TIME VIDEO ENCODING." Journal of Circuits, Systems and Computers 17, no. 04 (2008): 597–610. http://dx.doi.org/10.1142/s0218126608004563.

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Motion-JPEG2000 is derived from Part 1 of the JPEG2000 standard and provides high quality image compression in video coding system. This paper presents a real-time Motion-JPEG2000 encoding which is built on a fixed-point digital signal processor (DSP) as a single-chip implementation. The design addresses on the system-level design considerations. Among several modules in JPEG2000, Embedded Block Coding with Optimized Truncation (EBCOT) algorithm contains the highest computation complexity and also becomes the bottleneck of JPEG2000. Two speed-improved methods are proposed to significantly redu

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5

Zhang, Lu. "The Design of Static Image Compression System." Advanced Materials Research 1042 (October 2014): 150–53. http://dx.doi.org/10.4028/www.scientific.net/amr.1042.150.

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In this paper, a static image compression system based on DSP is introduced. The compression standard of this system is JPEG2000 that is the new image compression standard by ISO. First, the basic algorithm and key technologic of JPEG2000 are explained. Then, the realization method of the static image compression system based on JPEG2000 image coding is analyzed. Finally, the hardware of this system which is based on DSP is described. And by the verification of the system, very good static image compression effect can be get from this system.

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Dinu, Dragan, and Dragan Ivetic. "Architectures of DICOM based PACS for JPEG2000 medical image streaming." Computer Science and Information Systems 6, no. 1 (2009): 185–203. http://dx.doi.org/10.2298/csis0901185d.

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Delivering of medical image content to mobile/embedded devices with low storage and processing capabilities and low resolution displays is a challenging, but important task for achieving ubiquitous computing in modern hospital environments. The common approaches in industry and technical literature employ JPEG2000 compression and image streaming. Beside image compression, JPEG2000 facilitates image streaming. Different sized images are extracted from one codestream with minimal spatial distortion within decompressed image. We developed DICOM2000 syntax which enables JPEG2000 streaming over DIC

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7

LU, WEN, LIHUO HE, WENJIAN TANG, FEI GAO, and WEILONG HOU. "A NOVEL COMPRESSED IMAGES QUALITY METRIC." International Journal of Image and Graphics 11, no. 02 (2011): 281–92. http://dx.doi.org/10.1142/s021946781100410x.

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As the performance indicator of the image processing algorithms or systems, image quality assessment (IQA) has attracted the attention of many researchers. Aiming to the widely used compression standards, JPEG and JPEG2000, we propose a new no reference (NR) metric for compressed images to do IQA. This metric exploits the causes of distortion by JPEG and JPEG2000, employs the directional discrete cosine transform (DDCT) to obtain the detail and directional information of the images and incorporates with the visual perception to obtain the image quality index. Experimental results show that the

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8

Wang, Wei Ling. "JPEG2000 Image Compression Method Based on GPGPU." Advanced Materials Research 756-759 (September 2013): 1314–19. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.1314.

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In order to improve the compression speed of JPEG2000, the JPEG2000 compression standard is analysised and it concluded that the part data of the core algorithm that is DWT in JPEG2000 are independent from each other, so it is very suitable for parallel processing. CUDA (Compute Unified Device Architecture) is a latest software and hardware exploitation platform released by NVIDIA which is very suitable for large-scale data parallel computing.Using CUDA technology on general purpose graphic process unit (GPGPU) could speed up DWT algorithm parallelly and the program is optimized based on the c

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9

Marcellin, Michael W., and Ali Bilgin. "JPEG2000 for Digital Cinema." SMPTE Motion Imaging Journal 114, no. 5-6 (2005): 202–9. http://dx.doi.org/10.5594/j12291.

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10

Colyer, G. J., and R. A. Clark. "JPEG2000 and interactive applications." IEEE Transactions on Consumer Electronics 49, no. 4 (2003): 850–54. http://dx.doi.org/10.1109/tce.2003.1261165.

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11

Samet, Amine, Mohamed Ali Ben Ayed, Mourad Loulou, and Nouri Masmoudi. "Perceptual Evaluation of JPEG2000." European Transactions on Telecommunications 15, no. 2 (2004): 135–43. http://dx.doi.org/10.1002/ett.962.

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12

JACOB, THEJU, K. R. RAO, and DO NYEON KIM. "IMAGE MIRRORING AND ROTATION IN THE WAVELET DOMAIN." International Journal of Wavelets, Multiresolution and Information Processing 08, no. 01 (2010): 61–69. http://dx.doi.org/10.1142/s0219691310003389.

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JPEG2000, the international standard for still image compression, uses wavelet transform. The filters used by JPEG2000 for transformation are the 9/7 Daubechies filter and the 5/3 Le Gall filter. In this paper, we present a method for image mirroring and rotation in the wavelet domain, by manipulating the transformation coefficients. Our technique requires no additional complexity and the perfect reconstruction property is preserved.

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13

Adamović, Marko. "KOMPRESIJA MULTISPEKTRALNIH SATELITSKIH SNIMAKA KORIŠĆENJEM HEVC STANDARDA." Zbornik radova Fakulteta tehničkih nauka u Novom Sadu 34, no. 03 (2019): 594–97. http://dx.doi.org/10.24867/02be36adamovic.

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Sateliti za multispektralno snimanje Zemlje, kao što su američki Landsat 8 i evropski Sentinel-2, svakodnevno prave veliku količinu fotografija visoke rezolucije. Njihovo skladištenje zahteva veliki digitalni prostor, što uvećava cenu opreme. Landsat snima slike u nekompresovanom formatu, dok Sentinel koristi JPEG2000 kompresiju. Cilj ovog rada je da uporedi High Efficiency Video Coding (HEVC) i JPEG2000 standarde za kompresiju ovih fotografija i utvrdi da li bi HEVC bio bolje rešenje.

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14

Cao, Zhipeng, Zhenzhong Wei, and Guangjun Zhang. "A No-Reference Sharpness Metric Based on Structured Ringing for JPEG2000 Images." Advances in Optical Technologies 2014 (June 24, 2014): 1–13. http://dx.doi.org/10.1155/2014/295615.

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This work presents a no-reference image sharpness metric based on human blur perception for JPEG2000 compressed image. The metric mainly uses a ringing measure. And a blurring measure is used for compensation when the blur is so severe that ringing artifacts are concealed. We used the anisotropic diffusion for the preliminary ringing map and refined it by considering the property of ringing structure. The ringing detection of the proposed metric does not depend on edge detection, which is suitable for high degraded images. The characteristics of the ringing and blurring measures are analyzed a

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15

Tang, Ning, Jin Cai, and Yuan Li. "An Enhanced Resolution Three-Dimensional Transformation Method Based on Discrete Wavelet Transform." Applied Mechanics and Materials 159 (March 2012): 41–45. http://dx.doi.org/10.4028/www.scientific.net/amm.159.41.

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With the development of interactive multimedia technologies, image and video compression algorithms necessitated a number of better performance and functionality. Wavelet transform based embedded image coding method is the basis of JPEG2000. Lossy image compression algorithms sacrifice perfect image reconstruction in favor of decreased storage requirements. JPEG2000 algorithm has been developed based on the discrete wavelet transform (DWT) techniques, which have shown how the results achieved in different areas in information technology can be applied to enhance the performance.

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16

Zhu, Yaohua, Ya Liu, Yanghang Zhu, Mingsheng Huang, Jingyu Jiang, and Yong Zhang. "Lossy Infrared Image Compression Based on Wavelet Coefficient Probability Modeling and Run-Length-Enhanced Huffman Coding." Sensors 25, no. 8 (2025): 2491. https://doi.org/10.3390/s25082491.

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Infrared line-scanning images have high redundancy and large file sizes. In JPEG2000 compression, the MQ arithmetic encoder’s complexity slows down processing. Huffman coding can achieve O(1) complexity based on a code table, but its integer-bit encoding mechanism and ignorance of the continuity of symbol distribution result in suboptimal compression performance. In particular, when encoding sparse quantized wavelet coefficients that contain a large number of consecutive zeros, the inaccuracy of the one-bit shortest code accumulates, reducing compression efficiency. To address this, this paper

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17

Dr. R. B. Dubey, Dr R. B. Dubey, and Parul Parul. "Visually Lossless JPEG2000 Image Compression." Indian Journal of Applied Research 3, no. 9 (2011): 211–16. http://dx.doi.org/10.15373/2249555x/sept2013/66.

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18

Hussain, S. K., and G. Raja. "A JPEG 2000 BASED HYBRID IMAGE COMPRESSION TECHNIQUE FOR MEDICAL IMAGES." Nucleus 48, no. 4 (2011): 287–93. https://doi.org/10.71330/thenucleus.2011.822.

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Use of lossy compression for medical images could result in compression error that may be considered as diagnostic problem by medical doctor. Hybrid schemes, a combination of lossy and lossless compression are used to achieve higher compression ratio without compromising the subjective quality of medical images. This paper proposes a new hybrid compression method for medical images. Different combinations of lossy and lossless compression schemes: RLE, LZW, JPEG LS, JPEG and JPEG2000 are implemented to find out the best hybrid compression combination by keeping subjective quality of medical im

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19

Andra, K., C. Chakrabarti, and T. Acharya. "A high-performance JPEG2000 architecture." IEEE Transactions on Circuits and Systems for Video Technology 13, no. 3 (2003): 209–18. http://dx.doi.org/10.1109/tcsvt.2003.809834.

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20

Zhenyu Wu, A. Bilgin, and M. W. Marcellin. "Error Resilient Decoding of JPEG2000." IEEE Transactions on Circuits and Systems for Video Technology 17, no. 12 (2007): 1752–57. http://dx.doi.org/10.1109/tcsvt.2007.904534.

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21

Taubman, D. S., and M. W. Marcellin. "JPEG2000: standard for interactive imaging." Proceedings of the IEEE 90, no. 8 (2002): 1336–57. http://dx.doi.org/10.1109/jproc.2002.800725.

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22

Campbell, Derrick S. "Scalable image registration with JPEG2000." Journal of Electronic Imaging 18, no. 1 (2009): 013009. http://dx.doi.org/10.1117/1.3099706.

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23

Po-Chyi Su and C. C. J. Kuo. "Steganography in JPEG2000 compressed images." IEEE Transactions on Consumer Electronics 49, no. 4 (2003): 824–32. http://dx.doi.org/10.1109/tce.2003.1261161.

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24

Engel, Dominik, Thomas Stütz, and Andreas Uhl. "A survey on JPEG2000 encryption." Multimedia Systems 15, no. 4 (2009): 243–70. http://dx.doi.org/10.1007/s00530-008-0150-0.

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25

Ebner, M., G. Tischler, and J. Albert. "Integrating Color Constancy Into JPEG2000." IEEE Transactions on Image Processing 16, no. 11 (2007): 2697–706. http://dx.doi.org/10.1109/tip.2007.908086.

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26

Han Oh, Ali Bilgin, and Michael W. Marcellin. "Visually Lossless Encoding for JPEG2000." IEEE Transactions on Image Processing 22, no. 1 (2013): 189–201. http://dx.doi.org/10.1109/tip.2012.2215616.

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27

Chen, Tzong-Jer, Sheng-Chieh Lin, You-Chen Lin, Ren-Gui Cheng, Li-Hui Lin, and Wei Wu. "JPEG2000 Still Image Coding Quality." Journal of Digital Imaging 26, no. 5 (2013): 866–74. http://dx.doi.org/10.1007/s10278-013-9603-x.

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28

Persson, Hannes, Anna Brunstrom, and Tony Ottosson. "Utilizing Cross-Layer Information to Improve Performance in JPEG2000 Decoding." Advances in Multimedia 2007 (2007): 1–10. http://dx.doi.org/10.1155/2007/24758.

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We focus on wireless multimedia communication and investigate how cross-layer information can be used to improve performance at the application layer, using JPEG2000 as an example. The cross-layer information is in the form of soft information from the physical layer. The soft information, which is supplied by a soft decision demodulator, yields reliability measures for the received bits and is fed into two soft input iterative JPEG2000 image decoders. When errors are detected with the error detecting mechanisms in JPEG2000, the decoders utilize the soft information to point out likely transmi

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29

Hayati, Anis Kamilah, and Haris Suka Dyatmika. "THE EFFECT OF JPEG2000 COMPRESSION ON REMOTE SENSING DATA OF DIFFERENT SPATIAL RESOLUTIONS." International Journal of Remote Sensing and Earth Sciences (IJReSES) 14, no. 2 (2018): 111. http://dx.doi.org/10.30536/j.ijreses.2017.v14.a2724.

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The huge size of remote sensing data implies the information technology infrastructure to store, manage, deliver and process the data itself. To compensate these disadvantages, compressing technique is a possible solution. JPEG2000 compression provide lossless and lossy compression with scalability for lossy compression. As the ratio of lossy compression getshigher, the size of the file reduced but the information loss increased. This paper tries to investigate the JPEG2000 compression effect on remote sensing data of different spatial resolution. Three set of data (Landsat 8, SPOT 6 and Pleia

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30

Natsheh, Sahar, and Mousa Farajallah. "Classification of JPEG2000 Image Encryption Algorithms." Journal of Data Analytics and Engineering Decision Making 1, no. 1 (2024): 01–09. https://doi.org/10.33140/jdaedm.01.01.04.

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Image encryption is different from text encryption; as a result of the bulk data capacity, high redundancy of image data, and the high correlation between the image pixels. Thus, traditional methods are difficult to be used for image encryption as their pseudo-random sequences have a small period without real modification, which causes a restriction in the security and encryption of the image. Different types of JPEG2000 encryption techniques are addressed and discussed in secured and compressed (friendly) based aspects. Moreover, a study of JPEG2000 codec in terms of encryption is achieved in

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31

Lu, Liang, Leng Zhang, and Ting Zhang. "JPEG2000-Based Optimization Algorithm for Effective Compression Display of Remote Sensing Images." Applied Mechanics and Materials 325-326 (June 2013): 1602–9. http://dx.doi.org/10.4028/www.scientific.net/amm.325-326.1602.

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Taking the compression issue of remote sensing images as the study subject, this paper analyses the technical process for JPEG2000 compression and the image features of remote sensing images, natural images and figural images, and puts forwards an integrative optimization algorithm for effective compression display for remote sensing images based on common JPEG2000 compression frame. Thereinto, it includes high-frequency component filtering treatment, parallel processing of bit plane coding pass scanning and improved ROI coding algorithm, which give obvious clews to both overall consumed time

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32

Fukuhara, Takahiro. "Motion JPEG2000 and MJ2 File Format." Journal of The Institute of Image Information and Television Engineers 65, no. 8 (2011): 1177–80. http://dx.doi.org/10.3169/itej.65.1177.

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33

Juang, Ying-Shen, Hsi-Chin Hsin, Tze-Yun Sung, Yaw-Shih Shieh, and Carlo Cattani. "A Rate-Distortion-Based Merging Algorithm for Compressed Image Segmentation." Computational and Mathematical Methods in Medicine 2012 (2012): 1–7. http://dx.doi.org/10.1155/2012/648320.

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Original images are often compressed for the communication applications. In order to avoid the burden of decompressing computations, it is thus desirable to segment images in the compressed domain directly. This paper presents a simple rate-distortion-based scheme to segment images in the JPEG2000 domain. It is based on a binary arithmetic code table used in the JPEG2000 standard, which is available at both encoder and decoder; thus, there is no need to transmit the segmentation result. Experimental results on the Berkeley image database show that the proposed algorithm is preferable in terms

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34

Cho, Sang-Gyu, Zoran Bojkovic, Dragorad Milovanovic, Jungsik Lee, and Jae-Jeong Hwang. "Image quality evaluation: JPEG 2000 versus intra-only H.264/AVC High Profile." Facta universitatis - series: Electronics and Energetics 20, no. 1 (2007): 71–83. http://dx.doi.org/10.2298/fuee0701071c.

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The objective of this work is to provide image quality evaluation for intra-only H.264/AVC High Profile (HP) standard versus JPEG2000 standard. Here, we review the structure of the two standards and the coding algorithms in the context of subjective and objective assessments. Simulations were performed on a test set of monochrome and color image. As a result of simulations, we observed that the subjective and objective image quality of H.264/AVC is superior to JPEG2000, except the blocking artifact which is inherent, since it consists of block transform rather than whole image transform. Thus,

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35

Chang, Zhiguo, and Jian Xu. "Format-Compliant Encryption of JPEG2000 Codestreams." International Journal of Wireless and Microwave Technologies 1, no. 3 (2011): 54–61. http://dx.doi.org/10.5815/ijwmt.2011.03.09.

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36

Maini, Raman, and Suruchi Mehra. "A Review on JPEG2000 Image Compression." International Journal of Computer Applications 11, no. 9 (2010): 43–47. http://dx.doi.org/10.5120/1607-2159.

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37

Sanchez, V., and M. K. Mandal. "Efficient Channel Protection for JPEG2000 Bitstream." IEEE Transactions on Circuits and Systems for Video Technology 14, no. 4 (2004): 554–58. http://dx.doi.org/10.1109/tcsvt.2004.825573.

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38

Auli-Llinas, F., and J. Serra-Sagrista. "JPEG2000 Quality Scalability Without Quality Layers." IEEE Transactions on Circuits and Systems for Video Technology 18, no. 7 (2008): 923–36. http://dx.doi.org/10.1109/tcsvt.2008.920748.

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39

Minsoo Rhu and In-Cheol Park. "Optimization of Arithmetic Coding for JPEG2000." IEEE Transactions on Circuits and Systems for Video Technology 20, no. 3 (2010): 446–51. http://dx.doi.org/10.1109/tcsvt.2009.2031401.

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40

Long, M., H. M. Tai, and S. Yang. "Quantisation step selection schemes in JPEG2000." Electronics Letters 38, no. 12 (2002): 547. http://dx.doi.org/10.1049/el:20020375.

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41

Tsutsui, Hiroshi, Takahiko Masuzaki, Yoshiteru Hayashi, et al. "Design Framework For JPEG2000 System Architecture." Intelligent Automation & Soft Computing 12, no. 3 (2006): 331–43. http://dx.doi.org/10.1080/10798587.2006.10642936.

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42

Leibo Liu, Ning Chen, Hongying Meng, Li Zhang, Zhihua Wang, and Hongyi Chen. "A VLSI architecture of JPEG2000 encoder." IEEE Journal of Solid-State Circuits 39, no. 11 (2004): 2032–40. http://dx.doi.org/10.1109/jssc.2004.831492.

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43

Bing-Fei Wu and Chung-Fu Lin. "An efficient architecture for JPEG2000 coprocessor." IEEE Transactions on Consumer Electronics 50, no. 4 (2004): 1183–89. http://dx.doi.org/10.1109/tce.2004.1362517.

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Chebil, F., M. K. Bel Hadj Miled, A. Islam, and Kai Willner. "Compressed domain editing of JPEG2000 images." IEEE Transactions on Consumer Electronics 51, no. 2 (2005): 710–17. http://dx.doi.org/10.1109/tce.2005.1468023.

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Bilgin, A., M. W. Marcellin, and M. I. Altbach. "Compression of electrocardiogram signals using JPEG2000." IEEE Transactions on Consumer Electronics 49, no. 4 (2003): 833–40. http://dx.doi.org/10.1109/tce.2003.1261162.

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46

Li, L., Z. S. Wang, and M. Guo. "Adaptive rate control for Motion JPEG2000." IET Image Processing 3, no. 2 (2009): 75–87. http://dx.doi.org/10.1049/iet-ipr.2008.0053.

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47

Varma, K., and A. Bell. "JPEG2000 - choices and tradeoffs for encoders." IEEE Signal Processing Magazine 21, no. 6 (2004): 70–75. http://dx.doi.org/10.1109/msp.2004.1359144.

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48

Zhen Liu, L. J. Karam, and A. B. Watson. "JPEG2000 encoding with perceptual distortion control." IEEE Transactions on Image Processing 15, no. 7 (2006): 1763–78. http://dx.doi.org/10.1109/tip.2006.873460.

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49

Jicheng An and Zixing Cai. "Embedded Trellis Coded Quantization for JPEG2000." IEEE Transactions on Image Processing 17, no. 9 (2008): 1570–73. http://dx.doi.org/10.1109/tip.2008.2001157.

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Tan, D. M., C. S. Tan, and H. R. Wu. "Perceptual Color Image Coding With JPEG2000." IEEE Transactions on Image Processing 19, no. 2 (2010): 374–83. http://dx.doi.org/10.1109/tip.2009.2033625.

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