The Research Of PDE Based Image Filter And Image Blind Restoration And Their Applications In IVUS Image Processing

Digital image processing technique has been applied to many indus-tries. Advanced digital image processing techniques can not be applied without basic algorithm. This paper discuss several basic algorithms including image filter and image restoration, from both views of mathe-matic and engineering. Meanwhile, image processing in medical images, mainly in IVUS images has been discussed. The paper consists of three parts,In the first part, a newly developed filter which been called Guided Filter is discussed. And, the equivalent form which can be expressed in PDE is proposed. Experiments show that this newly formed technique can be used in many applications, including image smoothing, image de-haze and image contrast enhancement. Moreover, this newly developed style can bring more physical meaning. The Guided Filter is unified into a PDE based framework. This will help us to understand the algorithm more deeply and naturally. Further, this leads to new algorithms.In the second part, a new image blind deblurring algorithm is pro-posed. The algorithm is a novel and improved method to restore la-tent clear image from a single blurred image using some specifically se-lected image gradients. This algorithm uses an alternative minimization method to optimize the objective function and obtain both the latent image and the point spread function(PSF). Most state-of-the-art blind image restoration methods need a time-consuming and noise-prone step to predict the strong edges of latent images. A great contribution of the proposed method is that such a step is avoided since our method can estimate the PSF efficiently through selected image gradients. Because the estimation model of PSF is well-posed,this paper presents a much faster algorithm to achieve the PSF estimation function.In the third part, several basic techniques, mostly are the meth-ods proposed in this paper, are combined to solve the problems which appeared in IVUS image process. Firstly, the PGF filter is used to ac-complish the denoising task for the IVUS images. Because of the special characteristics of the PGF filter, the areas which have strong gradients are preserved. Then, the images are thrown into the segmentation algo-rithm which is developed from active contour model. When displaying the results, the blind deblurring technique is applied to synthesis a new image which has both the segment contour and a clear IVUS image. This is very helpful in disease diagnosis.