Entropy coders for image compression based on binary forward classification

Hoon Yoo; Jechang Jeong

doi:10.1117/12.411603

28 December 2000 Entropy coders for image compression based on binary forward classification

Hoon Yoo, Jechang Jeong

Proceedings Volume 4115, Applications of Digital Image Processing XXIII; (2000) https://doi.org/10.1117/12.411603
Event: International Symposium on Optical Science and Technology, 2000, San Diego, CA, United States

Abstract

Entropy coders as a noiseless compression method are widely used as final step compression for images, and there have been many contributions to increase of entropy coder performance and to reduction of entropy coder complexity. In this paper, we propose some entropy coders based on the binary forward classification (BFC). The BFC requires overhead of classification but there is no change between the amount of input information and the total amount of classified output information, which we prove this property in this paper. And using the proved property, we propose entropy coders that are the BFC followed by Golomb-Rice coders (BFC+GR) and the BFC followed by arithmetic coders (BFC+A). The proposed entropy coders introduce negligible additional complexity due to the BFC. Simulation results also show better performance than other entropy coders that have similar complexity to the proposed coders.

Citation Download Citation

Hoon Yoo and Jechang Jeong "Entropy coders for image compression based on binary forward classification", Proc. SPIE 4115, Applications of Digital Image Processing XXIII, (28 December 2000); https://doi.org/10.1117/12.411603

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