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A SVD based scheme for post processing of DCT coded images
Kumar Srivastava, Vinay (Motilal Nehru National Institute of Technology (Allahabad, Índia). Department of Electronics and Communication Engineering)

Data: 2009
Resum: In block discrete cosine transform (DCT) based image compression the blocking artifacts are the main cause of degradation, especially at higher compression ratio. In proposed scheme, monotone or edge blocks are identified by examining the DCT coefficients of the block itself. In the first algorithm of the proposed scheme, a signal adaptive filter is applied to sub-image constructed by the DC components of DCT coded image to exploit the residual inter-block correlation between adjacent blocks. To further reduce artificial discontinuities due to blocking artifacts, the blocky image is re-divided into blocks in such a way that the corner of the original blocks comes at the center of new blocks. These discontinuities cause the high frequency components in the new blocks. In this paper, these high frequency components due to blocking artifacts in monotone area are eliminated using singular value decomposition (SVD) based filtering algorithm. It is well known that random noise is hard to compress whereas it is easy to compress the ordered information. Thus, lossy compression of noisy signal provides the required filtering of the signal.
Drets: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades. Creative Commons
Llengua: Anglès.
Document: article ; recerca ; publishedVersion
Matèria: Image compression ; Image processing ; Post-processing ; Blocking artifacts ; DCT ; Singular value decomposition ; Block transform coding
Publicat a: ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 8, Núm. 3 ( 2009) , p. 1-14, ISSN 1577-5097

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DOI: 10.5565/rev/elcvia.160

14 p, 2.3 MB

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