A Coding Scheme for Noisy Image Based on Layer Segmentation

LI Tao; TIAN Xin; XIONG Chengyi; TIAN Jinwen

doi:10.1049/cje.2016.07.011

Volume 25 Issue 4

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LI Tao, TIAN Xin, XIONG Chengyi, et al., “A Coding Scheme for Noisy Image Based on Layer Segmentation,” Chinese Journal of Electronics, vol. 25, no. 4, pp. 700-705, 2016, doi: 10.1049/cje.2016.07.011

Citation:

LI Tao, TIAN Xin, XIONG Chengyi, et al., “A Coding Scheme for Noisy Image Based on Layer Segmentation,” Chinese Journal of Electronics, vol. 25, no. 4, pp. 700-705, 2016, doi: 10.1049/cje.2016.07.011

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A Coding Scheme for Noisy Image Based on Layer Segmentation

doi: 10.1049/cje.2016.07.011

1.
Nanjing Research Institute of Electronics Technology, Nanjing 210039, China;
2.
Wuhan University, Wuhan 430072, China;
3.
South-Central University for Nationalities, Wuhan 430074, China;
4.
Huazhong University of Science and Technology, Wuhan 430074, China

Funds: This work is supported by the National Natural Science Foundation of China (No.61102064, No.61471400), and the Chen-Guang Project of Wuhan City (No.2013072304010826).

More Information

Corresponding author: TIAN Xin (corresponding author) was born in Hubei, China, in 1982. He received his Ph.D. degree in control science and engineering from School of Automation, Huazhong University of Science and Technology, in 2010. Now he is a lecturer in Wuhan University. His research interests include image analysis, image compression and hardware implementation. (Email:xin.tian@whu.edu.cn)
Received Date: 2014-06-19
Rev Recd Date: 2014-09-03
Publish Date: 2016-07-10

Abstract

Abstract

Heavy noises distribute in the images when imaging in a poor environment. The randomness of noises makes pixels distributing singularly, which weakens the 1-D piecewise smooth property of original scenes. Thus, wavelets-based compression method no longer works well. In this paper, a layer segmentation based compression scheme is proposed for gray images. Image textures and some high frequency noises are described in a high frequency layer while the coarse part of the image is described in the low frequency layer. The high frequency layer is represented by a joint dictionary, and the low frequency layer is coded with the traditional wavelets. The proposed scheme is tested on nature images and synthetic images. The results show that the proposed scheme achieves better rate-distortion performance compared with several competing compression systems. Besides, further degradation of edges is avoided by the proposed compression scheme.
- Image coding,
- Noisy image model,
- Sparse representation,
- Edge detection

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References(13)

References

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