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1st International Conference on Technical Advancements in Computers and Communications (ICTACC)

作者： Nivedha, B. Priyadharshini, M. Thendral, E. Deenadayalan, T. KCG Coll Technol Dept Comp Sci & Engn Madras Tamil Nadu India

ISBN: (纸本)9781509047970

Huge numbers of images are produced today with advent of the 'big data' era. To store and transmit data traditional compression methods are no longer satisfying. In this paper, we face this challenge and to achieve a higher compression rate we are taking the advantage of the correlations existing between images. An image compression system that encodes each image by referencing its correlated images in the cloud. By comparing these features, we first extract features from an image and retrieve its similar image from the massive images in the cloud. Different methods of compressing point cloud data such as directly by converting it into 2D images or by using tree- based approaches have been explored from the previous studies. In this study, rather than compress point cloud data directly to compress the image in cloud data, by converting it lossless into range images, and then using various image compression algorithms to reduce the volume of the data.

关键词： compression methods longer satisfying reduce images lossless compression lossless image compression CLOUDS Clouds COMPRESSED imagery (Psychotherapy) image compression algorithm Cloud Computing Convert image two dimentional images Lossless compression ratio Reduce

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Quality Assessment of Deep-Learning-Based image compression 20

Quality Assessment of Deep-Learning-Based Image Compression

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20th IEEE International Workshop on Multimedia Signal Processing (MMSP)

作者： Valenzise, Giuseppe Purica, Andrei Hulusic, Vedad Cagnazzo, Marco Univ Paris Sud Cent Supelec CNRS L2SUMR 8506 F-91192 Gif Sur Yvette France Telecom ParisTech LTCI F-75013 Paris France Bournemouth Univ Fac Sci & Technol Dept Creat Technol Bournemouth Dorset England

ISBN: (纸本)9781538660706

image compression standards rely on predic coding. transform coding, quantization and entropy coding, in order to achieve high compression performance. Very recently, deep generative models have been used to optimize or replace some of these operations, with very promising results. However. so far no systematic and independent study of the coding performance of these algorithms has been carried out. In this paper, for the first time, we conduct a subjective evaluation of two recent deep learning-based image compression algorithnts, comparing them to JPEG 2000 and to the recent BPG image codec based on HEVC Intra. We found that compression approaches based on deep auto -encoders can achieve coding performance higher than JPEG 2000, and sometimes as good as BPG. We also show experimentally that the PSNR metric to be avoided when evaluating the visual quality of deep -learning-based methods, as artifacts have different characteristics from those of DCT or wavelet -based codecs. In particular, images compressed at low biirate appear more natural than JPEG 2000 coded pictu according to a no -reference naturalness measure. Our study indicates that deep generative models are likely to bring huge innovation into the video coding arena in the coming years.

关键词： JPEG Data compression image compression Quality assessment image compression algorithm Entropy coding Independent study codecs subjective evaluation discrete cosine transforms DCT gene

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A new approach for CCSDS image compression recommendation for multicomponent images to China-Brasil earth resources satellite

A new approach for CCSDS image compression recommendation fo...

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IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015

作者： Prata, Oscavo G. Pinho, Marcelo S. Instituto Tecnológico de Aeronáutica Sao José dos Campos SP Brazil

ISBN: (纸本)9781479979295

This paper presents a method for improving the performance of the compression algorithm recommended by CCSDS, operating with mutlicomponent images on lossy mode. The proposed method uses: KLT as the transform coding, an algorithm for distribute maximum bit rate between image components to maximize the PSNR, and a transport mechanism for transform coding coefficients. To evaluate the performance of the proposed method, images captured by the CCD camera of CBERS-2B were used. It was observed that the proposed method presents gains that can be of the order of 5 [dB] compared to the recommended algorithm being used to encode each image component independently. Furthermore, the results obtained demonstrate that the use of a fixed operator results in a performance close to that achieved by a computed transformation operator for each picture to be coded, for rates between 2 and 4 bit per pixel. © 2015 IEEE.

关键词： CCD image sensors image coding CBERS-2B CCD camera China-Brasil Earth resource satellite computed transformation operator image compression algorithm lossy mode multicomponent images recommended algorithm transform coding coefficients Discrete wavelet transforms image coding Redundancy Satellites Standards Transform coding CCSDS image compression Karhunen-Loéve Transform Multicomponent image consultative committee for space data systems image coding transform coding image compression algorithm Data compression image compression CCD image sensors discrete wavelet transform satellites redundancy Karhunen-Loeve transform compression algorithms

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Group Testing for Wavelet Packet image compression

Group Testing for Wavelet Packet image compression

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Data compression Conference (DCC 2001)

作者： Hong, ES Ladner, RE Riskin, EA Univ Washington Dept Comp Sci & Engn Seattle WA 98195 USA

ISBN: (纸本)0769510310

This paper introduces Group Testing for Wavelet Packets (GTWP), a novel embedded image compression algorithm based on wavelet packets and group testing. This algorithm extends the Group Testing for Wavelets (GTW) algorithm [7] to handle wavelet packets. Like its predecessor, GTWP obtains good compression performance without the use of arithmetic coding. It also shows that the group testing methodology is very flexible and can be applied in many different circumstances.

关键词： Group Testing Wavelet packets image compression algorithm arithmetic coding image compression Data compression

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Hardware-software co-design architecture for Joint Photo Expert Graphic XR encoder

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IET image PROCESSING 2012年第9期6卷 1284-1292页

作者： Tseng, C. -F. Lai, Y. -T. Natl Cheng Kung Univ Dept Elect Engn Tainan 701 Taiwan

In recent years, because of to the fast growing of internet and digital multi-media, new image compression algorithms are needed to reduce the transferring bandwidth and the decay of image quality. Joint Photo Expert Graphic (JPEG) extended range (XR) is a new standard for still image compression. Compared to previous standards, it provides better image quality and plentiful pixel format. However, the better image quality often comes with the higher computation complexity. In this study, the authors propose a hardware-software co-design architecture for JPEG XR encoder. For photo overlap transform (POT), and photo core transform (PCT), the complicated parts of JPEG XR, the authors propose new algorithms which eliminate data dependency in the basic filters of POT and PCT so that operations can be executed in parallel. The processing rate of the new algorithms is much faster. The authors also demonstrate a basic filter with multiple functions, which can be time-shared by POT and PCT;the hardware cost can be therefore reduced. Moreover, a memory saving scheme is proposed. Therefore the proposed architecture is suitable for stand-alone application-specific integrated circuit (ASIC). In our co-design, POT and PCT are implemented in hardware and then mapped to field programmable gate array (FPGA), whereas the other procedures of JPEG XR such as quantisation are executed by ARM926-EJ processor. The overall performance of our hardware architecture is 50 fps for 4:4:4 HDTV format at 166 MHz.

关键词： frequency 166 MHz image quality ASIC Filtering methods in signal processing photo core transform ARM926-EJ processor data compression hardware-software codesign digital multimedia image compression algorithm JPEG XR encoder field programmable gate arrays Hardware-software codesign Internet Electronic engineering computing FPGA joint photo expert graphic XR encoder Computer vision and image processing techniques computer architecture image and video coding still image compression application specific integrated circuits image coding hardware architecture photo overlap transform data dependency Integral transforms POT quantisation (signal) Logic circuits Computer architecture computation complexity quantisation JPEG extended range stand-alone application-specific integrated circuit PCT Logic and switching circuits memory saving scheme HDTV format filtering theory filter bandwidth transfer hardware-software co-design architecture field programmable gate array Digital circuit design, modelling and testing transforms

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BLOCK TRUNCATION CODING WITH ENTROPY CODING

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IEEE TRANSACTIONS ON COMMUNICATIONS 1995年第2-4期43卷 1677-1685页

作者： FRANTI, P NEVALAINEN, O Department of Computer Science University of Turku Turku Finland

Block Truncation Coding (ETC) is a simple and fast image compression algorithm which achieves constant bit rate of 2.0 bits per pixel, The method is however suboptimal. In the present paper we propose a modification of ETC in which the compression ratio will be improved by coding the quantization data and the bit plane by arithmetic coding with an adaptive modelling scheme. The results compare favorable with other ETC variants. The bit rate for test image Lena is 1.53 bits per pixel with the mean square error of 16.51.

关键词： compression ratio constant bit rate (CBR) pixel image compression algorithm Entropy coding arithmetic coding Mean square error Block truncation coding

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UltraSparc I: A four-issue processor supporting multimedia

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IEEE MICRO 1996年第2期16卷 42-50页

作者： Tremblay, M OConnor, JM Sun Microelectronics USA

UItraSpare I is a second-generation superscalar processor. It is a high performance, highly integrated, four issue superscalar processor based on the Spare Version 9 64-bit RISC architecture. We have extended the core instruction set to include graphics instructions that provide the most common operations related to two dimensional image processing; two- and three-dimensional graphics and image compression algorithms; and parallel operations on pixel data with 8-, 16-, and 32-bit components. Additional, new memory access instructions support the very high bandwidth requirements typical of graphics and multimedia applications.

关键词： graphic images UltraSPARC bandwidth requirement two dimentional images solid figure image compression algorithm MULTIMEDIA APPLICATION MULTI-MEDIA SYSTEM instruction PROCESSOR superscalar processor parallel operation

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USING VECTOR QUANTIZATION FOR image-PROCESSING

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PROCEEDINGS OF THE IEEE 1993年第9期81卷 1326-1341页

作者： COSMAN, PC OEHLER, KL RISKIN, EA GRAY, RM UNIV WASHINGTON DEPT ELECT ENGN SEATTLE WA 98195 USA

image compression is the process of reducing the number of bits required to represent an image. Vector quantization, the mapping of pixel intensity vectors into binary vectors indexing a limited number of possible reproductions, is a popular image compression algorithm. compression has traditionally been done with little regard for image processing operations that may precede or follow the compression step. Recent work has used vector quantization both to simplify image processing tasks-such as enhancement, classification, halftoning, and edge detection-and to reduce the computational complexity by performing them simultaneously with the compression. After briefly reviewing the fundamental ideas of vector quantization, we present a survey of vector quantization algorithms that perform image processing.

关键词： classification computational complexity edge detection edge detection enhancement halftoning image coding image compression algorithm image processing image processing pixel intensity vector mapping reviews vector quantisation vector quantization

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Imaging via compressive sampling

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IEEE SIGNAL PROCESSING MAGAZINE 2008年第2期25卷 14-20页

作者： Romberg, Justin CALTECH Dept Appl & Computat Math Pasadena CA 91125 USA

image compression algorithms convert high-resolution images into a relatively small bit streams in effect turning a large digital data set into a substantially smaller one. This article introduces compressive sampling... 详细信息

关键词： convex programming data compression image coding compressive sampling image compression image recovery convex programming image compression image coding image compression algorithm Sampling Data compression bit stream

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Enhanced Three-dimensional Color Conversion based on Discrete Wavelet Transform

Enhanced Three-dimensional Color Conversion based on Discret...

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2nd International Conference on Mechanical Engineering and Green Manufacturing (MEGM 2012)

作者： Yan, He Wang, Xiufeng Shaanxi Univ Sci & Technol Sch Mat Sci & Engn Xian Peoples R China

ISBN: (纸本)9783037853771

JPEG2000 algorithm has been developed based on the DWT techniques, which have shown how the results achieved in different areas in information technology can be applied to enhance the performance. Lossy image compression algorithms sacrifice perfect image reconstruction in favor of decreased storage requirements. Wavelets have become a popular technology for information redistribution for high-performance image compression algorithms. Lossy compression algorithms sacrifice perfect image reconstruction in favor of improved compression rates while minimizing image quality lossy.

关键词： Three-dimensional Transformation Discrete Wavelet Transform (DWT) image compression algorithm

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