At The Same Time De-noising And Contrast Enhancement Algorithm Research

Gray image denoising and contrast enhancement are two main contents in image processing technology fields and commonly used to improve the image quality. In practical processing, most of algorithms often set them independently, that is, denoising followed by enhancement or enhancement followed by denoising. To some extent, both of them will expand image noise or destroy image details. This thesis has an in-depth discussion and research on simultaneous algorithm of gray image denoising and contrast enhancement based on PDE.The basic contents and common methods of image denoising and contrast enhancement are summarized. In this thesis, it focuses on the methods of piecewise linear stretching function, denoising algorithm and image restoration based on TV. And numerical realization method is also given out.On the basis of researching the concept model of simultaneous denoising and contrast enhancement first proposed by Sapiro, the simultaneous algorithm of denoising and contrast enhancement is designed. By contrast to the traditional algorithms, the results showed that the new algorithms could have better effects for gray image with both low contrast and noise.A new method is proposed which can achieve dual function of simultaneous denoising and contrast enhancement based on TV image restoration model. The problem of simultaneous denosing and contrast enhancement is changed into a problem of image restoration. And an improved model is given out, the corresponding algorithm is also designed. Through the contrast experiments of artificial datas and real images, the results show that the new algorithm is better than traditional algorithms based on improved model.In order to give the quantitative evaluation of the output results and aim at the specific problem of image denoising and contrast enhancement, the mathematical morphology criterion based on image level set is used.