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Proceedings Paper

An approach to integrate the human vision psychology and perception knowledge into image enhancement
Author(s): Hui Wang; Xifeng Huang; Jiang Ping
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Paper Abstract

Image enhancement is very important image preprocessing technology especially when the image is captured in the poor imaging condition or dealing with the high bits image. The benefactor of image enhancement either may be a human observer or a computer vision process performing some kind of higher-level image analysis, such as target detection or scene understanding. One of the main objects of the image enhancement is getting a high dynamic range image and a high contrast degree image for human perception or interpretation. So, it is very necessary to integrate either empirical or statistical human vision psychology and perception knowledge into image enhancement. The human vision psychology and perception claims that humans' perception and response to the intensity fluctuation δu of visual signals are weighted by the background stimulus u, instead of being plainly uniform. There are three main laws: Weber's law, Weber- Fechner's law and Stevens's Law that describe this phenomenon in the psychology and psychophysics. This paper will integrate these three laws of the human vision psychology and perception into a very popular image enhancement algorithm named Adaptive Plateau Equalization (APE). The experiments were done on the high bits star image captured in night scene and the infrared-red image both the static image and the video stream. For the jitter problem in the video stream, this algorithm reduces this problem using the difference between the current frame's plateau value and the previous frame's plateau value to correct the current frame's plateau value. Considering the random noise impacts, the pixel value mapping process is not only depending on the current pixel but the pixels in the window surround the current pixel. The window size is usually 3×3. The process results of this improved algorithms is evaluated by the entropy analysis and visual perception analysis. The experiments' result showed the improved APE algorithms improved the quality of the image, the target and the surrounding assistant targets could be identified easily, and the noise was not amplified much. For the low quality image, these improved algorithms augment the information entropy and improve the image and the video stream aesthetic quality, while for the high quality image they will not debase the quality of the image.

Paper Details

Date Published: 5 August 2009
PDF: 8 pages
Proc. SPIE 7383, International Symposium on Photoelectronic Detection and Imaging 2009: Advances in Infrared Imaging and Applications, 73830A (5 August 2009); doi: 10.1117/12.834956
Show Author Affiliations
Hui Wang, Institute of Optics and Electronics (China)
Graduate Univ. of Chinese Academy of Sciences (China)
Xifeng Huang, Institute of Optics and Electronics (China)
Graduate Univ. of Chinese Academy of Sciences (China)
Jiang Ping, Institute of Optics and Electronics (China)


Published in SPIE Proceedings Vol. 7383:
International Symposium on Photoelectronic Detection and Imaging 2009: Advances in Infrared Imaging and Applications
Jeffery Puschell; Hai-mei Gong; Yi Cai; Jin Lu; Jin-dong Fei, Editor(s)

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