DocumentCode
1325706
Title
Visual sensitivity-based low-bit-rate image compression algorithm
Author
Xia, Qing ; Li, Xin ; Zhuo, Lu ; Lam, K.M.
Author_Institution
Signal & Inf. Process. Lab., Beijing Univ. of Technol., Beijing, China
Volume
6
Issue
7
fYear
2012
fDate
10/1/2012 12:00:00 AM
Firstpage
910
Lastpage
918
Abstract
In this study, the authors present a visual sensitivity-based low-bit-rate image compression algorithm. The authors algorithm combines both visual sensitivity and compression techniques so that a higher compression rate, with satisfactory visual quality, can be achieved. In the coding process, the input image is divided into blocks, and each block is classified as an edge block (EB), a textural block (TB) or a flat block (FB). For EBs, which are most important to the subjective quality of decoded images, the standard Joint Photographic Experts Group (JPEG) coding scheme with a tolerant quantisation step is employed so as to restrict the blocking artefacts caused by the quantisation error to an acceptable level. For FBs, a skipping scheme is employed on blocks in the compression process so as to save the bits. The coding of the skip blocks, identified by the skipping scheme, will make reference to the reconstructed regions of the image in the encoding process. Owing to the masking effects of the human visual system on high-frequency textures, standard JPEG compression coding with a greater quantisation step is employed on the down-scaled version of non-skip blocks and TBs. Experimental results show the superior performance of our method in terms of both compression efficiency and visual quality.
Keywords
block codes; data compression; image classification; image coding; image reconstruction; image texture; quantisation (signal); JPEG coding scheme; Joint Photographic Experts Group; blocking artefacts; edge block classification; flat block classification; high-frequency textures; image reconstruction regions; quantisation error; skip block coding; skipping scheme; standard JPEG compression coding; textural block classification; visual quality; visual sensitivity-based low-bit-rate image compression algorithm;
fLanguage
English
Journal_Title
Image Processing, IET
Publisher
iet
ISSN
1751-9659
Type
jour
DOI
10.1049/iet-ipr.2011.0174
Filename
6336962
Link To Document