Research And Implementation On Visible Image Enhancement Method Based On Partial Differential Equation

Image information has already became the main and important way which we recognize and know the world. And image information processing is also used by people in all aspects of life and work. Image enhancement processing as one of the important part of image information processing becomes the main study object of researchers. This paper mainly studies on visible image enhancement method based on partial differential equation and the implementation process. By analyzing the basic theoretical knowledge of the method of partial differential equation, and combining the image enhancement theory, discuss some of the important and hot and difficult problems of the field of image processing, and solve practical engineering application problems.Firstly, this paper introduces the main application and the research significance of partial differential equation in image processing, and summarizes the development process and the research status of the image processing based on partial differential equation, analyzes of the advantages of the image processing method. Then this paper briefly reviews the traditional methods of image enhancement, and analyzes their advantages and disadvantages. This paper focuses on the research of the visible image enhancement method based on partial differential equation. Image enhancement as an important step link between the past, focused on several aspects of the visible image degraded image quality improvement reasons. First, this paper analyzes and discusses the nonlinear anisotropic diffusion model-PM model which was first used in the field of image denoising. The PM model is improved for the image edge blur because of image denoising, the new diffusion function can not only remove noise of the image but also preserving the edge and texture very well. Then considering the disadvantage of the image contrast enhancement method by gradient field equalization and the method of enhancing the image contrast and brightness, this paper combines with the partial differential equation and the adjustable histogram equalization method, and enhances the image edge and improves the visual effect of the image brightness. In the numerical solution process, discrete finite difference method, and combine with the heat equation greatly reduces the amount of computation and shorten the running time. The improved PDE-based visible image enhancement method is transplanted to the hardware, and does systematic and comprehensive optimization improvements combining with the characteristics of the hardware platform. Finally it reaches the real-time image enhancement algorithm requirements for a wide range of engineering applications and provides a guarantee for the image processing.