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IMAGE PROCESSING, PATTERN RECOGNITION
Statistical encoding for image compression based on hierarchical grid interpolation
M. V. Gashnikov Samara National Research University, Samara, Russia
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.
Received: 26.07.2017 Accepted: 23.09.2017
Citation:
M. V. Gashnikov, “Statistical encoding for image compression based on hierarchical grid interpolation”, Computer Optics, 41:6 (2017), 905–912
Linking options:
https://www.mathnet.ru/eng/co464 https://www.mathnet.ru/eng/co/v41/i6/p905
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Abstract page: | 138 | Full-text PDF : | 57 | References: | 30 |
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