Relevant bibliographies by topics / Image compression

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Image compression'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Image compression"

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Er., Neha Saini Mr. Naveen Dhillion Mr. Manit Kapoor. "A PAPER ON A COMPARATIVE STUDY BLOCK TRUNCATING CODING, WAVELET, FRACTAL IMAGE COMPRESSION & EMBEDDED ZERO TREE." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 7 (2016): 1052–61. https://doi.org/10.5281/zenodo.57987.

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Many different image compression techniques currently exist for the compression of different types of images. Image compression is fundamental to the efficient and cost-effective use of digital imaging technology and applications. In this study Image compression was applied to compress and decompress image at various compression ratios. Compressing an image is significantly different than compressing raw binary data. For this different compression algorithm are used to compress images. Fractal image compression has been widely used to compress the image.  We undertake a study of the perfo
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Saudagar, Abdul Khader Jilani. "Biomedical Image Compression Techniques for Clinical Image Processing." International Journal of Online and Biomedical Engineering (iJOE) 16, no. 12 (2020): 133. http://dx.doi.org/10.3991/ijoe.v16i12.17019.

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Image processing is widely used in the domain of biomedical engineering especially for compression of clinical images. Clinical diagnosis receives high importance which involves handling patient’s data more accurately and wisely when treating patients remotely. Many researchers proposed different methods for compression of medical images using Artificial Intelligence techniques. Developing efficient automated systems for compression of medical images in telemedicine is the focal point in this paper. Three major approaches were proposed here for medical image compression. They are image compres
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Kanimozhirajasekaran*1, &. P. D. Sathya2. "AN EFFICIENT OPTIMIZATION TECHNIQUE FOR FRACTAL IMAGE COMPRESSION OF MEDICAL IMAGE." GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES 5, no. 2 (2018): 97–103. https://doi.org/10.5281/zenodo.1404141.

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Medical images plays a vital role in the area of medicine. It is important to store the medical images for future reference. So, there is a need for compressing of medical images for storage and communication purpose. Over the last few decades, many image compression methods have been introduced. They gives high compression ratio with loss of quality of image. Medical imagesshould always be stored in lossless format.There are several lossless compression techniques using which, original images can be restored.The objective of image compression is to reduce the redundancy of the 
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Khan, Sulaiman, Shah Nazir, Anwar Hussain, Amjad Ali, and Ayaz Ullah. "An efficient JPEG image compression based on Haar wavelet transform, discrete cosine transform, and run length encoding techniques for advanced manufacturing processes." Measurement and Control 52, no. 9-10 (2019): 1532–44. http://dx.doi.org/10.1177/0020294019877508.

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Image compression plays a key role in the transmission of an image and storage capacity. Image compression aims to reduce the size of the image with no loss of significant information and no loss of quality in the image. To reduce the storage capacity of the image, the image compression is proposed in order to offer a compact illustration of the information included in the image. Image compression exists in the form of lossy or lossless. Even though image compression mechanism has a prominent role for compressing images, certain conflicts still exist in the available techniques. This paper pre
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David S, Alex, Almas Begum, and Ravikumar S. "Content clustering for MRI Image compression using PPAM." International Journal of Engineering & Technology 7, no. 1.7 (2018): 126. http://dx.doi.org/10.14419/ijet.v7i1.7.10631.

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Image compression helps to save the utilization of memory, data while transferring the images between nodes. Compression is one of the key technique in medical image. Both lossy and lossless compressions where used based on the application. In case of medical imaging each and every components of pixel is very important hence its nature to chose lossless compression medical images. MRI images are compressed after processing. Here in this paper we have used PPMA method to compress the MRI image. For retrieval of the compressed image content clustering method used.
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Walaa, M. Abd-Elhafiez, Gharibi Wajeb, and Heshmat Mohamed. "An efficient color image compression technique." TELKOMNIKA Telecommunication, Computing, Electronics and Control 18, no. 5 (2020): 2371~2377. https://doi.org/10.12928/TELKOMNIKA.v18i5.8632.

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We present a new image compression method to improve visual perception of the decompressed images and achieve higher image compression ratio. This method balances between the compression rate and image quality by compressing the essential parts of the image-edges. The key subject/edge is of more significance than background/non-edge image. Taking into consideration the value of image components and the effect of smoothness in image compression, this method classifies the image components as edge or non-edge. Low-quality lossy compression is applied to non-edge components whereas high-quality l
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Katayama, O., S. Ishihama, K. Namiki, and I. Ohi. "Color Changes in Electronic Endoscopic Images Caused by Image Compression." Diagnostic and Therapeutic Endoscopy 4, no. 1 (1997): 43–50. http://dx.doi.org/10.1155/dte.4.43.

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In recent years, recording of color still images into magneto–optical video disks has been increasingly used as a method for recording electronic endoscopic images. In this case, image compression is often used to reduce the volume and cost of recording media and also to minimize the time required for image recording and playback. With this in mind, we recorded 8 images into a magneto-optical video disk in 4 image compression modes (no compression, weak compression, moderate compression, and strong compression) using the Joint Photographic Image Coding Experts Group (JPEG) system, which is a w
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Cardone, Barbara, Ferdinando Di Martino, and Salvatore Sessa. "Fuzzy Transform Image Compression in the YUV Space." Computation 11, no. 10 (2023): 191. http://dx.doi.org/10.3390/computation11100191.

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This research proposes a new image compression method based on the F1-transform which improves the quality of the reconstructed image without increasing the coding/decoding CPU time. The advantage of compressing color images in the YUV space is due to the fact that while the three bands Red, Green and Blue are equally perceived by the human eye, in YUV space most of the image information perceived by the human eye is contained in the Y band, as opposed to the U and V bands. Using this advantage, we construct a new color image compression algorithm based on F1-transform in which the image compr
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Kaur, Gaganpreet, Hitashi Hitashi, and Dr Gurdev Singh. "PERFORMANCE EVALUATION OF IMAGE QUALITY BASED ON FRACTAL IMAGE COMPRESSION." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 2, no. 1 (2012): 20–27. http://dx.doi.org/10.24297/ijct.v2i1.2608.

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Fractal techniques for image compression haverecently attracted a great deal of attention. Fractalimage compression is a relatively recenttechnique based on the representation of animage by a contractive transform, on the space ofimages, for which the fixed point is close to theoriginal image. This broad principle encompassesa very wide variety of coding schemes, many ofwhich have been explored in the rapidly growingbody of published research.Unfortunately, littlein the way of practical algorithms or techniqueshas been published. Here present a technique forimage compression that is based on a
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Kryvenko, Sergii, Vladimir Lukin, Boban Bondžulić, and Nenad Stojanović. "COMPRESSION OF NOISY GRAYSCALE IMAGES WITH COMPRESSION RATIO ANALYSIS." Advanced Information Systems 9, no. 2 (2025): 68–74. https://doi.org/10.20998/2522-9052.2025.2.09.

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The object of the study is the process of compressing noisy images in a lossy manner by better portable graphics (BPG) encoder. The subject of the study is the method for adaptive selection of the coder parameter Q depending on noise intensity and image complexity. The goal of the study is to consider the basic characteristics of lossy compression of remote sensing images contaminated by additive white Gaussian noise with giving recommendations of preferable Q setting. Methods used: numerical simulation, verification for test images. Results obtained: 1) the dependencies of compression ratio o
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Dissertations / Theses on the topic "Image compression"

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Hawary, Fatma. "Light field image compression and compressive acquisition." Thesis, Rennes 1, 2019. http://www.theses.fr/2019REN1S082.

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En capturant une scène à partir de plusieurs points de vue, un champ de lumière fournit une représentation riche de la géométrie de la scène, ce qui permet une variété de nouvelles applications de post-capture ainsi que des expériences immersives. L'objectif de cette thèse est d'étudier la compressibilité des contenus de type champ de lumière afin de proposer de nouvelles solutions pour une imagerie de champs lumière à plus haute résolution. Deux aspects principaux ont été étudiés à travers ce travail. Les performances en compression sur les champs lumière des schémas de codage actuels étant e
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Obaid, Arif. "Range image compression." Thesis, University of Ottawa (Canada), 1995. http://hdl.handle.net/10393/10131.

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Range Images, which are a representation of the surface of a 3-D object, are gaining popularity in many applications including CAD/CAM, multimedia and virtual reality. There is, thus, a need for compression of these 3-D images. Current standards for still image compression, such as JPEG, are not appropriate for such images because they have been designed specifically for intensity images. This has led us to develop a new compression method for range images. It first scans the image so that the pixels are arranged into a sequence. It then approximates this sequence by straight line segments wit
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Lacroix, Bruno. "Fractal image compression." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ36939.pdf.

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Aydinoğlu, Behçet Halûk. "Stereo image compression." Diss., Georgia Institute of Technology, 1997. http://hdl.handle.net/1853/15447.

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Abdul-Amir, Said. "Digital image compression." Thesis, De Montfort University, 1985. http://hdl.handle.net/2086/10681.

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Due to the rapid growth in information handling and transmission, there is a serious demand for more efficient data compression schemes. compression schemes address themselves to speech, visual and alphanumeric coded data. This thesis is concerned with the compression of visual data given in the form of still or moving pictures. such data is highly correlated spatially and in the context domain. A detailed study of some existing data compression systems is presented, in particular, the performance of DPCM was analysed by computer simulation, and the results examined both subjectively and objec
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Hallidy, William H. Jr, and Michael Doerr. "HYPERSPECTRAL IMAGE COMPRESSION." International Foundation for Telemetering, 1999. http://hdl.handle.net/10150/608744.

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International Telemetering Conference Proceedings / October 25-28, 1999 / Riviera Hotel and Convention Center, Las Vegas, Nevada<br>Systems & Processes Engineering Corporation (SPEC) compared compression and decompression algorithms and developed optimal forms of lossless and lossy compression for hyperspectral data. We examined the relationship between compression-induced distortion and additive noise, determined the effect of errors on the compressed data, and showed that the data could separate targets from clutter after more than 50:1 compression.
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Hernández-Cabronero, Miguel. "DNA Microarray Image Compression." Doctoral thesis, Universitat Autònoma de Barcelona, 2015. http://hdl.handle.net/10803/297706.

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En los experimentos con DNA microarrays se genran dos imágenes monocromo, las cuales es conveniente almacenar para poder realizar análisis más precisos en un futuro. Por tanto, la compresión de imágenes surge como una herramienta particularmente útil para minimizar los costes asociados al almacenamiento y la transmisión de dichas imágenes. Esta tesis tiene por objetivo mejorar el estado del arte en la compresión de imágenes de DNA microarrays. Como parte de esta tesis, se ha realizado una detallada investigación de las características de las imágenes de DNA microarray. Los resultados experi
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Agostini, Luciano Volcan. "Projeto de arquiteturas integradas para a compressão de imagens JPEG." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2002. http://hdl.handle.net/10183/11431.

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Esta dissertação apresenta o desenvolvimento de arquiteturas para a compressão JPEG, onde são apresentadas arquiteturas de um compressor JPEG para imagens em tons de cinza, de um compressor JPEG para imagens coloridas e de um conversor de espaço de cores de RGB para YCbCr. As arquiteturas desenvolvidas são detalhadamente apresentadas, tendo sido completamente descritas em VHDL, com sua síntese direcionada para FPGAs da família Flex10KE da Altera. A arquitetura integrada do compressor JPEG para imagens em tons de cinza possui uma latência mínima de 237 ciclos de clock e processa uma imagem de 6
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Nicholl, Peter Nigel. "Feature directed spiral image compression : (a new technique for lossless image compression)." Thesis, University of Ulster, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.339326.

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Mandal, Mrinal Kumar. "Wavelets for image compression." Thesis, University of Ottawa (Canada), 1995. http://hdl.handle.net/10393/10277.

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Wavelets are becoming increasingly important in image compression applications because of its flexibility in representing nonstationary signals. To achieve a high compression ratio, the wavelet has to be adapted to the image. Current techniques use exhaustive search procedures which are computationally intensive to find the optimal basis (type/order/tree) for the image to be coded. In this thesis, we have carried out extensive performance analysis of various wavelets on a wide variety of images. Based on the investigation, we propose some guidelines for searching for the optimal wavelet (type/
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Books on the topic "Image compression"

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Pearlman, William A. Wavelet Image Compression. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-031-02248-7.

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Kou, Weidong. Digital Image Compression. Springer US, 1995. http://dx.doi.org/10.1007/978-1-4757-2361-8.

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Fisher, Yuval, ed. Fractal Image Compression. Springer New York, 1995. http://dx.doi.org/10.1007/978-1-4612-2472-3.

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Shukla, K. K., and M. V. Prasad. Lossy Image Compression. Springer London, 2011. http://dx.doi.org/10.1007/978-1-4471-2218-0.

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Barnsley, Michael. Fractal image compression. AK Peters, 1993.

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Barnsley, Michael. Fractal image compression. AK Peters, 1993.

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Storer, James A. Image and Text Compression. Springer US, 1992.

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Storer, James A., ed. Image and Text Compression. Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-3596-6.

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1953-, Storer James A., ed. Image and text compression. Kluwer Academic, 1992.

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S, Carasso Alfred, and National Institute of Standards and Technology (U.S.), eds. Image compression and deblurring. U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, 2000.

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Book chapters on the topic "Image compression"

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Salomon, David. "Image Compression." In Data Compression. Springer New York, 1998. http://dx.doi.org/10.1007/978-1-4757-2939-9_4.

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Salomon, David. "Image Compression." In Data Compression. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-86092-8_5.

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Sha, Lei. "Image Compression." In Encyclopedia of GIS. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_584.

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Walnut, David F. "Image Compression." In An Introduction to Wavelet Analysis. Birkhäuser Boston, 2004. http://dx.doi.org/10.1007/978-1-4612-0001-7_12.

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Mann, Stephen. "Image Compression." In PACS. Springer New York, 2002. http://dx.doi.org/10.1007/978-1-4757-3651-9_10.

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Sha, Lei. "Image Compression." In Encyclopedia of GIS. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-23519-6_584-2.

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Salomon, David, and Giovanni Motta. "Image Compression." In Handbook of Data Compression. Springer London, 2009. http://dx.doi.org/10.1007/978-1-84882-903-9_7.

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Sundararajan, D. "Image Compression." In Digital Image Processing. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-6113-4_13.

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Salomon, David. "Image Compression." In A Guide to Data Compression Methods. Springer New York, 2002. http://dx.doi.org/10.1007/978-0-387-21708-6_4.

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Weik, Martin H. "image compression." In Computer Science and Communications Dictionary. Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_8640.

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Conference papers on the topic "Image compression"

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Tang, Luyang, Yongqi Zhai, and Ronggang Wang. "Compression-Aware Tuning for Compressing Volumetric Radiance Fields." In 2024 IEEE International Conference on Image Processing (ICIP). IEEE, 2024. http://dx.doi.org/10.1109/icip51287.2024.10647954.

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Aczel, Till, and Roger Wattenhofer. "Conditional Hallucinations for Image Compression." In 2025 Data Compression Conference (DCC). IEEE, 2025. https://doi.org/10.1109/dcc62719.2025.00043.

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Ni, Weifeng, Tianqiu Pu, and Yuxi Wang. "Application of Lossless Compression Method in Image Compression." In 2024 IEEE 7th International Conference on Information Systems and Computer Aided Education (ICISCAE). IEEE, 2024. https://doi.org/10.1109/iciscae62304.2024.10761882.

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Li, Hui, Yan Lu, Masahiro Takei, Mitsuaki Ochi, Yoshifuru Saito, and Kiyoshi Horii. "Flow Image Compression Using Wavelets." In ASME 1999 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/imece1999-1212.

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Abstract The wavelet compression technique was applied to turbulent image processing for reducing physical storage and extracting the compact dominant features in this study. The two compression methods, called zone and threshold compression, were employed. It was found that a high order wavelet basis provided good compression performance for compressing turbulent images and two compression methods exhibited almost same performance. It was realized that the compressed image had both lower compress ratio and larger correlation coefficients. By changing compression ratio the compressed images ex
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Yi Yang, Oscar C. Au, Lu Fang, Xing Wen, and Weiran Tang. "Reweighted Compressive Sampling for image compression." In 2009 Picture Coding Symposium (PCS). IEEE, 2009. http://dx.doi.org/10.1109/pcs.2009.5167354.

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B. Al-Obaidi, Marwa, Ghadah Al-Khafaji, and Mohammed M. Siddeq. "Enhancing Color Image Compression with Linear Polynomial Coding and Adaptive Inter-Prediction." In 5TH INTERNATIONAL CONFERENCE ON COMMUNICATION ENGINEERING AND COMPUTER SCIENCE (CIC-COCOS'24). Cihan University-Erbil, 2024. http://dx.doi.org/10.24086/cocos2024/paper.1524.

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This paper introduces a proposed technique for compressing color images with the objective of minimizing their size. The technique divides the image into three bands: a source band representing the Green channel, and a non-source band representing the Red and Blue channels. The source band is encoded using a lossless 2D_linear polynomial technique, which ensures that the compressed image retains its original quality. The non-source bands employ an adaptive inter-prediction technique to enhance the efficiency of compression. The experimental results provide evidence supporting the effectiveness
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Deng, Chenwei, Weisi Lin, Bu-sung Lee, and Chiew Tong Lau. "Robust image compression based on compressive sensing." In 2010 IEEE International Conference on Multimedia and Expo (ICME). IEEE, 2010. http://dx.doi.org/10.1109/icme.2010.5583387.

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Hubbard-Featherstone, Casey J., Mark A. Garcia, and William Y. L. Lee. "Adaptive block compressive sensing for image compression." In 2017 International Conference on Image and Vision Computing New Zealand (IVCNZ). IEEE, 2017. http://dx.doi.org/10.1109/ivcnz.2017.8402490.

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Li, Hui, Masahiro Takei, Yoshifuru Saito, and Kiyoshi Horii. "Application of Wavelet Packet to Particle Image Velocimetry Technique." In ASME 2000 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/imece2000-2090.

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Abstract Our motive of this study is to develop an application of the wavelet packet to PIV image compression processing in order to improve the spatial resolution and reliability furthermore. It was found that the reconstructed PIV image with a lower compression ratio may emphasize particle edges at a relatively high spatial resolution, and the reconstructed PIV image with a higher compression ratio may display the large-scale motion of particles and may deduce noisy. In this study, the relative error of the wavelet packet image compression technique was lower than that of the standard wavele
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McGuire, Michael D. "Is Fractal Image Compression Related to Cortical Image Compression?" In Applied Vision. Optica Publishing Group, 1989. http://dx.doi.org/10.1364/av.1989.wb4.

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Fractals are customarily introduced with simple line replacement rules, for example the well known Koch curve. At each state of iteration single lines are replaced by combinations of lines according to a rule. Remarkable complexity can be built up this way as shown by five stages of this line replacement bush fractal1.
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Reports on the topic "Image compression"

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NETROLOGIC INC SAN DIEGO CA. Image Compression. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada224242.

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Wang, Jun, and H. K. Huang. Digital Mammographic Image Compression. Defense Technical Information Center, 1995. http://dx.doi.org/10.21236/ada300271.

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Nakassis, Anastase, and Alfred Carasso. Image compression and deblurring. National Institute of Standards and Technology, 2000. http://dx.doi.org/10.6028/nist.ir.6521.

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Boss, R. D., and E. W. Jacobs. Fractal-Based Image Compression. Defense Technical Information Center, 1989. http://dx.doi.org/10.21236/ada215400.

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Jacobs, E. W., R. D. Boss, and Y. Fisher. Fractal-Based Image Compression, II. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada226500.

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Reynolds, W. D. Jr. Image compression using the W-transform. Office of Scientific and Technical Information (OSTI), 1995. http://dx.doi.org/10.2172/195703.

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Mazieres, Bertrand. A New Approach for Fingerprint Image Compression. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/763151.

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Hodges, Dewey H. AASERT-92/Image Compression & Wavelet Generation. Defense Technical Information Center, 1996. http://dx.doi.org/10.21236/ada337454.

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Libert, John M. Guidance on Contactless Friction Ridge Image Compression. National Institute of Standards and Technology, 2023. http://dx.doi.org/10.6028/nist.ir.8465.

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Libert, John M. Guidance on Contactless Friction Ridge Image Compression. National Institute of Standards and Technology, 2023. http://dx.doi.org/10.6028/nist.sp.500-340.

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