Statistical encoding for image compression based on hierarchical grid interpolation
Gashnikov M.V.

 

Samara National Research University, Samara, Russia

Full text of article: Russian language.

Abstract:
Algorithms of statistical encoding for image compression are investigated. An approach is proposed to increase the efficiency of variable-length codes when compressing images with losses. An algorithm of statistical encoding is developed for use as part of image compression methods that encode a de-correlated signal with an uneven probability distribution. An experimental comparison of the proposed algorithm with the algorithms ZIP and ARJ is performed while encoding the specific data of the hierarchical compression method. In addition, an experimental comparison of the hierarchical method of image compression, including the developed coding algorithm, with the JPEG method and the method based on the wavelet transform is carried out.

Keywords:
image compression, statistical encoding, variable length codes, quantization, entropy, compressed data size.

Citation:
Gashnikov MV. Statistical encoding for image compression based on hierarchical grid interpolation. Computer Optics 2017; 41(6): 905-912. DOI: 10.18287/2412-6179-2017-41-6-905-912.

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