Image Smoothing And Enhancement Algorithm Based On Partial Differential Equation

In recent years, image analysis and processing methods based on PDE and diffusion driven by geometric curvature flow has been interested in markedly. PDE algorithm is a fine method in image analysis and processing and can be used in many aspects, such as noise reduction, image enhancement and segmentation.This dissertation focuses on the variation problem and PDE in image processing applications. And the study is carried out in image restoration, image enhancement, image super-resolution and image inpainting based on total variation. Following is the outline of the dissertation.The major application of PDE in image processing and its value to research are introduced A review- to the history and actuality of image processing based on PDE is presented additionally. Focus on image enhancing in resolution based on shock filters. Usually, reaction-diffusion equations for image smoothing are parabolic partial differential equations. In Super-resolution is a branch of image processing. It is an important and inexpensive method to improve image quality. Noise and blurred edges will be added to image by using general interpolation method during image enlargement. Here, super-resolution algorithm based on shock filter and anisotropic diffusion is proposed. Image inpainting is a small branch of image restoration and it is a hot topic in digital image processing field. Through a normal and undetectable way, image inpainting aims to produce a revised image, photo or video. And the inpainted region is seamlessly immerged into the original image. Because of interference, noise and channel congestion, bit error and package loss are always inevitable in communications. So, it becomes worse to reconstruct video frames at a receiver. Erring signals can be concealed by making use of space-time redundancy and vision features, and image inpainting can do this work well. General method of inpainting is to interpolate. In this chapter, image inpainting based on total variation is focused on. In addition, an algorithm for local image inpainting and global enhancing is proposed.