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Soft Compression for Lossless Image Coding Based on Shape Recognition.

Authors :
Xin, Gangtao
Fan, Pingyi
Source :
Entropy. Dec2021, Vol. 23 Issue 12, p1680-1680. 1p.
Publication Year :
2021

Abstract

Soft compression is a lossless image compression method that is committed to eliminating coding redundancy and spatial redundancy simultaneously. To do so, it adopts shapes to encode an image. In this paper, we propose a compressible indicator function with regard to images, which gives a threshold of the average number of bits required to represent a location and can be used for illustrating the working principle. We investigate and analyze soft compression for binary image, gray image and multi-component image with specific algorithms and compressible indicator value. In terms of compression ratio, the soft compression algorithm outperforms the popular classical standards PNG and JPEG2000 in lossless image compression. It is expected that the bandwidth and storage space needed when transmitting and storing the same kind of images (such as medical images) can be greatly reduced with applying soft compression. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10994300
Volume :
23
Issue :
12
Database :
Academic Search Index
Journal :
Entropy
Publication Type :
Academic Journal
Accession number :
154371575
Full Text :
https://doi.org/10.3390/e23121680