A Study of Adaptive Contrast Enhancement base on Fuzzy Set Algorithm Technology

• Main Authors: Rong-Nan Lin, 林榮楠
• Other Authors: Hsueh-Yi Lin
• Format: Others
• Language: zh-TW
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/08367698288758674765

碩士 === 國立勤益科技大學 === 電子工程系 === 103 === Image processing application has become an integral part of everyday life, much of this information is required for analysis by image processing. But image grab is often caused by different light distribution of different image quality, such as: overexposure, underexposure, low contrast and high contrast image…etc. Resulting in the loss details information of image area. Image enhancement technology is to improve weakly detail information from images. Common image enhancement technology including Histogram Equalization, Contrast Stretching method, S-Curve scheme, Power Function adjustment and Gamma Correction method …etc. This study is based on the fuzzy theory, analysis and study of image enhancement method. There are to improve overexposed and underexposed image to enhance by choose adaptive threshold value, row and column local enhancement and using Power Function to modified membership value. Analysis of exposure value to determine image characteristics of the image is overexposed or underexposed, then using fuzzy theory principle of image enhancement to change membership, overexposed areas of contrast ratio to cut down, underexposed areas of comparative value to raise up, to achieve the effect of adaptive image enhancement. Experimental results show that the method can smooth and soft contrast enhancement, and matches the human visual perception.