123452 678) 9:; 3?@ABC!;DE. A`5ab &QcdeA2!8fg hiji5 k!`E. U#, RGB de!l8mJn o(`5?@!]^%12Aabpq1rANO !sP_5 k!tu#E. v 345 12Aw1r xyz{ $%B H#Q, &) K|}z{sP% 1r LM K &L5~ #E. L5'()* p6WJ k L(=ADCP '()* EHz{ K & `E. AbstractIt is difficult to use a recognition algorithm of an image in a foggy environment because the color and edge information is removed. One of the famous defogging algorithm is haze removal by using ‘Dark Channel Prior(DCP)’ which is used to predict for transmission rate using color information of an image and eliminates fog from the image. However, in case that the image has factors such as sunset or yellow dust, there is overemphasized problem on the color of certain channel after haze removal. Furthermore, in case that the image includes an object containing high RGB channel, the transmission related to this area causes a misestimated issue. In this paper, we purpose an enhanced fog elimination algorithm by using improved color normalization and haze rate revision which correct mis-estimation haze area on the basis of color information and edge information of an image. By eliminating the color distortion, we can obtain more natural clean image from the haze image.Keyword : Dark channel, Haze removal, Color normalization, Interpolation