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Image Denoising via Control of Curvature Continuity and Its Application

Author: DiJianTao
Tutor: YangXunNian
School: Zhejiang University
Course: Applied Mathematics
Keywords: Sharpening factor Scaling factor Median filter Anisotropic filtering Bilateral Filtering Homogeneous bilateral filtering Denoising Smooth The image surface model
CLC: TP391.41
Type: Master's thesis
Year: 2008
Downloads: 72
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The Image Denoising is one of the fundamental problem in image processing, is the basis of many applications in image processing and computer vision. In this paper, the surface of the image A characterization of local image smoothing metric, to establish a new metric discrete surface noise-free image representation equation. Two new image denoising algorithm based on the noise image model and image local smoothness measure. This article both denoising algorithm can remove a variety of image noise, and effective to maintain the boundary information of the image, to prevent the contraction of the image gray value in the smoothing processing. The full text of the main include the following aspects: the first part, based on the the curvature continuous image denoising algorithm. The measure of image smoothness sharpening factor is defined based on the ratio of the the discrete normal curvature of the image surface, and distinguish image noise pixels based sharpening factor and non-noise pixels criteria. Finally, by sharpening factor calculation and standardization, and the use of noise-free image representation equation gives a curvature continuity control image denoising algorithm. The algorithm reconstruction from noisy data noise-free image, and thus a variety of image noise removal, also good to keep the details of the image characteristics. With the increase in the number of iterations, the algorithm, denoising results converge to a steady state, effective to prevent the gray value of the image contraction. The second part, the image of the homogeneous the bilateral filtering algorithms. Based on sharpening the image smoothing factor standard bilateral filtering to maintain the advantages of the boundary homogeneous bilateral filtering. Bilateral filtering linear prediction, homogeneous bilateral algorithm based on curvature continuity to predict noise pixel color values ??in the the same denoising parameters, the new algorithm can remove more substantial noise. The Homogeneous bilateral filtering can be multiple iterations of the filtering process to resolve bilateral filtering can not be many iterations. In addition, this new algorithm removing noise while maintaining the image more detail, and effective solution to the traditional bilateral filtering is easy to produce sub-block phenomenon. The third part of this paper the application of the two filtering methods. This paper presents two filtering algorithm used in the field of image interpolation and edge detection. The classic image interpolation algorithm bilinear interpolation and bicubic interpolation compared this algorithm is better to keep the original image details and effectively solve the the serrated problem of image interpolation algorithm. In the field of edge detection, we mainly on the original image filter pretreatment, and then use the canny operator to detect the boundary. Compared with the conventional pretreatment effect, this algorithm can be suppressed to a variety of noise and effective to maintain the boundary information of the original image.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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