11-09-2017, 01:29 PM
Diffuse logic and histogram-based algorithm to improve low-contrast color images and other contrast enhancement techniques using the concept of homomorphic filtering with fuzzy logic. These two methods have been compared with conventional contrast enhancement techniques. These methods are computationally fast compared to conventional and other advanced enhancement techniques. The performance of these contrast enhancement algorithms is evaluated based on visual quality, CII and computational time. The inter comparison of different techniques was carried out on different low contrast color images. Based on performance analysis, we advocate that the fuzzy logic-based method and the proposed histogram be suitable for improving the contrast of low-contrast color images and homomorphic filtering based on fuzzy logic is suitable for the contrast of gray images of low contrast.
To achieve these three image enhancement goals, we first develop filters that have excellent edge conservation capabilities but do not work well by smoothing Gaussian noise. We then modify the filters to perform the three image enhancement tasks. These filters are based on the idea that individual pixels should not be fired uniformly by each of the fuzzy rules. To demonstrate the capability of our filtering approach, it was tested on several different image enhancement issues. These experimental results demonstrate the speed, filter quality and sharpness of the new filter image.
To achieve these three image enhancement goals, we first develop filters that have excellent edge conservation capabilities but do not work well by smoothing Gaussian noise. We then modify the filters to perform the three image enhancement tasks. These filters are based on the idea that individual pixels should not be fired uniformly by each of the fuzzy rules. To demonstrate the capability of our filtering approach, it was tested on several different image enhancement issues. These experimental results demonstrate the speed, filter quality and sharpness of the new filter image.