数字图像处使用理英文文献翻译参考初版.doc

Hybrid Genetic Algorithm Based Image Enhancement Technology Mu Dongzhou Department of the Information Engineering XuZhou College of Industrial Technology XuZhou, China mudzh@ Xu Chao and Ge Hongmei Department of the Information Engineering XuZhou College of Industrial Technology XuZhou, China xuch@ , gehm@ Abstract—in image enhancement, Tubbs proposed a normalized incomplete Beta function to represent several kinds of commonly used non-linear transform functions to do the research on image enhancement. But how to define the coefficients of the Beta function is still a problem. We proposed a Hybrid Genetic Algorithm which combines the Differential Evolution to the Genetic Algorithm in the image enhancement process and utilize the quickly searching ability of the algorithm to carry out the adaptive mutation and searches. Finally we use the Simulation experiment to prove the effectiveness of the method. Keywords- Image enhancement; Hybrid Genetic Algorithm; adaptive enhancement I. INTRODUCTION In the image formation, transfer or conversion process, due to other objective factors such as system noise, inadequate or excessive exposure, relative motion and so the impact will get the image often a difference between the original image (referred to as degraded or degraded) Degraded image is usually blurred or after the extraction of information through the machine to reduce or even wrong, it must take some measures for its improvement. Image enhancement technology is proposed in this sense, and the purpose is to improve the image quality. Fuzzy Image Enhancement situation according to the image using a variety of special technical highlights some of the information in the image, reduce or eliminate the irrelevant information, to emphasize the image of the whole or the purpose of local features. Image enhancement method is still no unified theory, image enhancement techniques can be divided into three categories: point operations, and spatial frequency enhancement