Image Visual Enhancement Based on Layered Difference Representation

GENG Aihui; WAN Chunming; LI Yi; ZHANG Yunfeng; CAO Lihua; FENG Qiang

doi:10.11999/JEIT161070

Volume 39 Issue 4

Apr. 2017

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Article Navigation > Journal of Electronics & Information Technology > 2017 > 39(4): 922-929

GENG Aihui, WAN Chunming, LI Yi, ZHANG Yunfeng, CAO Lihua, FENG Qiang. Image Visual Enhancement Based on Layered Difference Representation[J]. Journal of Electronics & Information Technology, 2017, 39(4): 922-929. doi: 10.11999/JEIT161070

Citation:

GENG Aihui, WAN Chunming, LI Yi, ZHANG Yunfeng, CAO Lihua, FENG Qiang. Image Visual Enhancement Based on Layered Difference Representation[J]. Journal of Electronics & Information Technology, 2017, 39(4): 922-929. doi: 10.11999/JEIT161070

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Image Visual Enhancement Based on Layered Difference Representation

doi: 10.11999/JEIT161070

1.
2.
(Changchun University of Science and Technplogy, Changchun 130022, China)

Funds:

The National Natural Science Foundation of China (61205143), The Science and Technology Department of Jilin Province Research Funding (20110329)

Received Date: 2016-10-12
Rev Recd Date: 2017-02-15
Publish Date: 2017-04-19

Abstract

Abstract

Human vision pays more attention to the interesting region than other areas. A method based on salient region detection for layered difference representation of 2D histogram is proposed to achieve visual enhancement. The algorithm detects the salient region by salient filtering and cuts salient region with a threshold for visual perception firstly. Then, 2D histogram is calculated for related region in original image of salient region, and statistical information in different layers is converted to layer 2 according to the inner relationship of each layer. Following a difference vector is gained though solving a constrained optimization problem of layered difference representation at a specified layer. To preserve the character of non-salient region, an origin difference vector is defined. Finally, output image is reconstructed by a transformation function, which is the result of two difference vectors for salient region and non-salient region. Experimental results show that the proposed method enhances contrast and details in salient region efficiently while protecting non-salient region in origin image. The objective evaluation parameters in three group experiments illustrate that the proposed algorithm can get better scores in protecting global mean lighting in non-salient region, increasing PSNR and HSNR of the whole image compared to other five algorithms. The EME value of images enhanced by the proposed method is moderate. The objective evaluation parameters are consistent with the subject observation, and it demonstrates the proposed method can achieve visual enhancement effectively.
- Image processing,
- Vision enhancement,
- Salient detection,
- Layered difference representation,
- 2D histogram

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References(25)

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