维纳滤波实现图像恢复.docVIP

武汉理工大学 现代数字信号处理（论文） 摘 要 I Abstract II 1 绪论 1 1.1 研究背景及意义 1 1.2 国内外研究现状 2 2 运动模糊恢复理论基础 4 2.1 图像退化模型 4 2.1.1 连续退化模型 5 2.1.2离散函数退化模型 6 2.2 图像的恢复方法 9 2.2.1逆滤波复原法 9 2.2.2约束最小平方复原法 11 3 维纳滤波实现对退化图像的复原 13 3.1 维纳滤波的基本原理 13 3.2 维纳滤波对退化图像的恢复 14 4 实验仿真 16 5 总结和展望 18 致谢 20 Abstract With the development of science and technology, the requirement for image quality is higher than before. In particular condition, we cann’t get very clear image from the image acquisition device. There are many factors influencing the image quality, such as the low quality of image acquisition device. They result in the missing of image detail. Besides, the light intensity may lead to the reduction of image contrast. Our purpose is to get high quality image that contains large number of detais from the degraded image. In practical application, it’s more important to extra detail and edge information. We want to get the license information that offends vehicle, or the disease information. Thus, it’s necessary to improve image quality by restoration of the degraded image. Digital image restoration aims at constructing the original image from the degraded image. Motion blur is very common in various degraded pattern. When there is relative motion between the image acquisition device and the object, the motion blur occurs. It results in the degrade of image quality. We need to clear image by programming to get clear image. The thesis analyzes the causes of motion blur, and builds the degraded model. Then the estimation of motion blur parameters is introduced in the model, that contains blur angle and length estimation. At last, Wiener Filter is adopted for restoration. With the appearance of Ringing Effect, The whole image deblur process is completed. Analyze the causes of Ringing Effect in the image restoration, we conclude that noise is the main factor. In the process of obtaining、transporting and saving image, noise is inevitable. Thus, haar wavelet is used for denoising in image pre-proce