Efficient, Low-Complexity Image Coding With a Set-Partitioning Embedded Block Coder

Pearlman, William A.; Islam, Ashraful; Nagaraj, Nithin; Said, Amir

doi:10.1109/tcsvt.2004.835150

Cited by 328 publications

(188 citation statements)

References 13 publications

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“…An eventual open research work should be the adaptation of EBCOT to VSN constraints, taking advantage of some potential solutions to alleviate the workload and the complexity of the EBCOT algorithm. [46], where the authors suggest a compression algorithm that makes use of sets of pixels in the form of block when spanning wavelet subbands, instead of using trees as with EZW or SPIHT. SPECK algorithm starts by performing an appropriate subband transformation (usually, the DWT) on the input image, which allows its decomposition into a series of coefficients.…”

Section: Ebcot-based Schemes For Vsnmentioning

confidence: 99%

“…A listless variant of SPECK image compression called LSK is suggested in [48]. LSK uses the block-partitioning policies of SPECK and does an explicit breadth first search, without the need for lists as in [46] or [50]. State information is kept in an array of fixed size that corresponds to the array of coefficient values, with two bits per coefficient to enable fast scanning of the bit planes.…”

Section: Speck Background Speck Is Introduced Inmentioning

confidence: 99%

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A Survey of Image Compression Algorithms for Visual Sensor Networks

Mammeri

Hadjou

Khoumsi

2012

ISRN Sensor Networks

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With the advent of visual sensor networks (VSNs), energy-aware compression algorithms have gained wide attention. That is, new strategies and mechanisms for power-efficient image compression algorithms are developed, since the application of the conventional methods is not always energy beneficial. In this paper, we provide a survey of image compression algorithms for visual sensor networks, ranging from the conventional standards such as JPEG and JPEG2000 to a new compression method, for example, compressive sensing. We provide the advantages and shortcomings of the application of these algorithms in VSN, a literature review of their application in VSN, as well as an open research issue for each compression standard/method. Moreover, factors influencing the design of compression algorithms in the context of VSN are presented. We conclude by some guidelines which concern the design of a compression method for VSN.

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Section: Ebcot-based Schemes For Vsnmentioning

confidence: 99%

Section: Speck Background Speck Is Introduced Inmentioning

confidence: 99%

A Survey of Image Compression Algorithms for Visual Sensor Networks

Mammeri

Hadjou

Khoumsi

2012

ISRN Sensor Networks

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“…Since redundancies within the hyper-cube can be more effectively removed, lossy compression has been widely used by many researchers, using typical approaches including vector quantisation (VQ) (Mendenhall and Merenyi 2008;Qian et al 2001;Qian 2006;Li et al 2014), principal component analysis (PCA) (Du and Fowler 2007;Zabalza, Ren, Wang, Zhang, et al 2014;Ren et al 2014) and transform-domain approaches (Kim, Xiong, and Pearlman 2000;Pearlman et al 2004;Said and Pearlman 1996). In Chen's work (Chen 1998), it was found that although it is simple, the VQ approach is inappropriate for low bit rate compression.…”

Section: Introductionmentioning

confidence: 99%

Effective compression of hyperspectral imagery using an improved 3D DCT approach for land-cover analysis in remote-sensing applications

Qiao

Ren

Sun

et al. 2014

International Journal of Remote Sensing

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This version is available at https://strathprints.strath.ac.uk/50084/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the Strathprints administrator: strathprints@strath.ac.ukThe Strathprints institutional repository (https://strathprints.strath.ac.uk) is a digital archive of University of Strathclyde research outputs. It has been developed to disseminate open access research outputs, expose data about those outputs, and enable the management and persistent access to Strathclyde's intellectual output. Effective compression of hyperspectral imagery using an improved 3DDCT approach for land cover analysis in remote sensing applications Effective compression of hyperspectral imagery using an improved 3D DCT approach for land cover analysis in remote sensing applicationsAlthough hyperspectral imagery (HSI), which has been applied in a wide range of applications, suffers from very large volumes of data, its uncompressed representation is still preferred to avoid compression loss for accurate data analysis. In this paper, we focus on quality-assured lossy compression of HSI,where the accuracy of analysis from decoded data is taken as a key criterion to

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“…For two dimensions, starting with Shapiro's pioneering work on Embedded Zerotree Wavelet (EZW) coding [1] to the JPEG 2000 [2,3] image compression standard to the new 2D lossy-to-lossless compression algorithm recently standardized by the Consultative Committee for Space Data Systems (CCSDS) [4,5], SPC has served as an auxiliary component to the coding efficiency of wavelet-based approaches. SPC has also been successfully applied into several other well-known image coding algorithms including SPIHT [6], SPECK [7], SWEET [8], SBHP [9] and EZBC [10]. As an effective way of representing image data in the wavelet domain, SPC (sometimes combined with other entropy coding methods, such as arithmetic coding) takes advantage of the beneficial localization properties of wavelet transforms to achieve competitive rate-distortion performance.…”

Section: Introductionmentioning

confidence: 99%

Motion differential set partition coding for image sequence and video compression

Pearlman

2012

Journal of Visual Communication and Image Representation

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Efficient, Low-Complexity Image Coding With a Set-Partitioning Embedded Block Coder

Cited by 328 publications

References 13 publications

A Survey of Image Compression Algorithms for Visual Sensor Networks

A Survey of Image Compression Algorithms for Visual Sensor Networks

Effective compression of hyperspectral imagery using an improved 3D DCT approach for land-cover analysis in remote-sensing applications

Motion differential set partition coding for image sequence and video compression

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