scholarly journals Lossless Image Compression Based on Multiple-Tables Arithmetic Coding

2009 ◽  
Vol 2009 ◽  
pp. 1-13 ◽  
Author(s):  
Rung-Ching Chen ◽  
Pei-Yan Pai ◽  
Yung-Kuan Chan ◽  
Chin-Chen Chang

This paper is intended to present a lossless image compression method based on multiple-tables arithmetic coding (MTAC) method to encode a gray-level imagef. First, the MTAC method employs a median edge detector (MED) to reduce the entropy rate off. The gray levels of two adjacent pixels in an image are usually similar. A base-switching transformation approach is then used to reduce the spatial redundancy of the image. The gray levels of some pixels in an image are more common than those of others. Finally, the arithmetic encoding method is applied to reduce the coding redundancy of the image. To promote high performance of the arithmetic encoding method, the MTAC method first classifies the data and then encodes each cluster of data using a distinct code table. The experimental results show that, in most cases, the MTAC method provides a higher efficiency in use of storage space than the lossless JPEG2000 does.

Entropy ◽  
2021 ◽  
Vol 23 (12) ◽  
pp. 1680
Author(s):  
Gangtao Xin ◽  
Pingyi Fan

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.


1993 ◽  
Author(s):  
Krystyna Ohnesorge ◽  
Peter Stucki ◽  
Hartwig Thomas

2013 ◽  
Vol 321-324 ◽  
pp. 1219-1224
Author(s):  
Bao Tang Shan ◽  
Fa Nian Wang ◽  
Juan Gao

In order to improve the compression performance of Bayer CFA images exposed continuously, a new high performance remainder set near-lossless compression method is presented. Based on channel-separated-filtering, several typical Bayer CFA image compression methods are compared with the proposed remainder set algorithm. It is proved that the remainder set algorithm has not only the better compression performance, i.e., the lower bits per pixel (average about 2.16bpp), but also the better reconstructed CFA image PSNR (average about 52.31dB). Finally, the proposed method is employed in a multiple channel CMOS image sampling system and some test results are given.


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