Title: Using online dictionary learning to improve Bayer pattern image coding

Authors: Tingyi Zheng; Li Wang

Addresses: College of Computer Science and Technology, Taiyuan University of Technology, Shanxi, China; Department of Electrical and Power Engineering, Shanxi Institute of Energy, Shanxi, China ' College of Computer Science and Technology, Taiyuan University of Technology, Shanxi, China

Abstract: Image quality is a fundamental concern in image compression. There is a lot of noise in image compression process, which may impact on users not getting precise identification. It has, thus, always been neglected in image compression in the past researches. In fact, noise takes a beneficial role in image reconstruction. In this paper, we chose noise as considered and recommended as a coding method for Bayer pattern image based on online dictionary learning. Investigations have depicted that the proposed method in Bayer pattern image coding might develop the rate of distortion performance of Bayer pattern image coding at any rate.

Keywords: Bayer pattern image; online dictionary learning; ODL; rate distortion; image compression.

DOI: 10.1504/IJCSE.2018.090485

International Journal of Computational Science and Engineering, 2018 Vol.16 No.2, pp.132 - 140

Available online: 07 Mar 2018 *

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