Application Design Of Wavelet Thresholding Denoising Alogrithm Based On The Prior Model

In the engineering field, various image in sampling and data transmission process, will be noise interference of mechanical by nature, had different effect on the true features of images.Therefore, denoising plays a key role in the pretreatment of image, the accuracy of subsequent image processing and the application of the results.Based on orthogonal wavelet transform and stationary wavelet transform to do the analysis and denoising Matlab simulation theory, obtained by orthogonal wavelet denoising, image edge will appear oscillation distortion,distortion and stationary wavelet transform can be very good to improve the image of the edge. Then focuses on the a priori model of noisy image, this paper will be the first comprehensive analysis more comprehensive prior model. then denoised routine work breakdown, traditional, verified by simulation that, if combined with this method stationary wavelet transform,.Secondly, based on the prior theory and stationary wavelet transform,design a "digital image prior model and stationary wavelet transform denoising preprocessing prototype system based on". The system hasturned into, the digital image and zoom and other basic functions, and can be a prior algorithm and wavelet based denoising preprocessing function,and can be the edge feature extraction after work on the basis of imagepretreatment, to verify the denoising work plays an important role in the subsequent digital image processing, and deduces the pretreatment method can also be applied to image retrieval and other important research direction.Finally, the system testing and the functionality of the prototype system, the test results, the de-noising pretreatment prior image based on the theory of functions of the system, not only can improve the image quality in the smooth regions, distortion can also improve the image edge. This paper verified at the same time, the method of denoising preprocessing image based on edge feature extraction, achieved good results, so the denoising method by digital image in other engineering fields will be more quality promotion.