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Proceedings Paper

A local image enhancement method based on adjacent pixel gray order-preserving principle
Author(s): Xiaopeng Fan; Tiefeng Cai; Feng Zhu
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Paper Abstract

The paper is committed in local image enhancement. At first, the authors propose an adjacent pixel gray order-preserving principle. Adjacent pixel gray order-preserving principle is the basement of local enhancement method which ensures that there is no distortion in processed image. And then, the authors propose an iterative algorithm, which could stretch gray-scale difference of adjacent pixels in premise of not changing gray magnitude relationship between adjacent pixels. At last, the authors propose a totally reference image quality assessment method based on adjacent pixel gray order-preserving principle. According to this quality assessment method, the authors made a set of comparative experiments with local histogram equalization and method. Experimental results show that the proposed enhancement method can get higher score and provide better visual effects, fully demonstrating its effectiveness. According to this quality assessment method, the proposed method shows a good effectiveness, through experimental results and comparison with local histogram equalization method. Local contrast enhancement, adjacent pixel gray order-preserving principle, iterative algorithm, image quality assessment.

Paper Details

Date Published: 11 September 2013
PDF: 7 pages
Proc. SPIE 8907, International Symposium on Photoelectronic Detection and Imaging 2013: Infrared Imaging and Applications, 890723 (11 September 2013); doi: 10.1117/12.2032922
Show Author Affiliations
Xiaopeng Fan, Shenyang Institute of Automation (China)
Univ. of Chinese Academy of Sciences (China)
Key Lab. of Optical-Electronics Information Processing (China), Key Lab. of Image Understanding (China)
Tiefeng Cai, Shenyang Institute of Automation (China)
Univ. of Chinese Academy of Sciences (China)
Key Lab. of Optical-Electronics Information Processing (China), Key Lab. of Image Understanding (China)
Feng Zhu, Shenyang Institute of Automation (China)
Key Lab. of Optical-Electronics Information Processing (China)
Key Lab. of Image Understanding and Computer Vision (China)


Published in SPIE Proceedings Vol. 8907:
International Symposium on Photoelectronic Detection and Imaging 2013: Infrared Imaging and Applications
Haimei Gong; Zelin Shi; Qian Chen; Jin Lu, Editor(s)

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