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Proceedings Paper

Combined Peano scan and VQ approach to image compression
Author(s): Ashwin Sampath; Ahmad C. Ansari
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Paper Abstract

In order to achieve high compression ratios, while maintaining visual quality, a new approach combining Peano scanning and vector quantization is proposed. The Peano scan technique clusters highly correlated pixels, and a vector quantization scheme is developed to exploit interblock correlation. An efficient scan technique serves as a useful preprocessing unit in image compression. In this work, Peano curves are used locally to transform the original image into one containing clustered bands of correlated data. The Peano scan results in a much lower mean absolute difference between neighboring blocks than the Raster scan (almost 50% reduction) i.e., better reordering/clustering is achieved. A codebook is formed using the LBG algorithm. The clustered image is subdivided into blocks of 4 X 4 and vector quantized using the codebook. The pattern of indices of codevectors chosen for successive blocks is exploited. Due to clustering achieved, frequently the same codevector is used to encode a series of successive blocks. Transmission of the same codevector index for each block is inefficient. A method of assigning additional bits to encode the repeat pattern is proposed. This causes an overall reduction in bit-rate. Another technique employs dynamic partitioning of the codebook into a large passive part and a smaller active part. If the mean squared difference between successive blocks is below a predetermined threshold, only the active part is searched. This leads to lowering of bit-rate and search time. The combined approach suggested exploits interblock correlation in an image, using an efficient scan technique. It leads to lower bit-rates than conventional VQ methods, at comparable visual quality.

Paper Details

Date Published: 8 April 1993
PDF: 12 pages
Proc. SPIE 1903, Image and Video Processing, (8 April 1993); doi: 10.1117/12.143126
Show Author Affiliations
Ashwin Sampath, Rutgers Univ. (United States)
Ahmad C. Ansari, Rutgers Univ. (United States)


Published in SPIE Proceedings Vol. 1903:
Image and Video Processing
Majid Rabbani; M. Ibrahim Sezan; A. Murat Tekalp, Editor(s)

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