Study On Image Enhancement Method Based On Partial Differential Equation

Image as an effective information carrier, is the main source for people to obtain information and exchange information. So, digital image processing relates to all aspects of human life and the work. Image enhancement is an important aspect of image processing. It plays an important role in the whole process of image processing. This paper mainly studies on image enhancement method based on partial differential equation. By analyzing the theory of partial differential equation, and combining the image enhancement theory, discuss some difficult problems in the process of image processing, and put forward some methods to solve them.Firstly, this paper briefly reviews the traditional methods of image enhancement, and analyzes their advantages and disadvantages. According to the limitations of the traditional methods, the partial differential equation is introduced. Introducing the main application and the research significance of partial differential equation in image processing. Summarize the development process and the research status of the image processing based on partial differential equation. Secondly, this paper mainly discusses the image denoising methods based on partial differential equation. The diffusion models used in image denoising have mang forms. The first model is P-M nonlinear anisotropic diffusion model, which is put forward by Perona and Malik in 1990. It has far-reaching significance. This paper analyses the advantages and disadvantages of this model. According to the existing problems of P-M model, proposes a new diffusion function, which can not only remove noise of the image but also preserving the edge and texture very well. The SNR increases significantly. This paper focuses on the research of the image enhancement method based on partial differential equation. Enlighten by the great role of partial differential equation in image denoising, so partial differential equation is used into the image enhancement system. First, introduce the image contrast enhancement method by gradient field equalization proposed by Zhu Lixin and Xia Deshen. Then analyze the advantages and disadvantages of this method. This paper puts forward a new image enhancement method based on partial differential equation. In this method a new gradient transformation function is put forward, which can enhance the edge and the texture of the small gradient, make the weak texture details more clear. At the same time, in order to adjust the brightness and constrast of the image, combining the histogram equalization, put forward inverse equalization transformation. When histogram equalization and inverse equalization transformation combine together, the image brightness and contrast can be adjusted very well. This method can not only enhance the images whose edges and textures are not clear because of the defocusing of the camera, but also enhance the images whose brightness is uneven and contrast is low because of uneven illumination and the fog and other environmental impacts. It can make the details hidden in the dark background and the bright background more clear. So achieve a better visual effect. It is helpful for further image processing and video applications. This method has a very wide application scope.In addition, this paper uses the finite difference method to discrete the partial differential equation, and uses the least square principle to get euler equation. And heat equation is introduced to turn the direct solution to iteration form. Thus can greatly reduce computational complexity, and shorten the run time. It can provids a guarantee for realizing the real-time image processing.