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Super-Resolution Image Reconstruction

Posted on:2011-10-28Degree:MasterType:Thesis
Country:ChinaCandidate:B B ZhangFull Text:PDF
GTID:2178360305470564Subject:Pattern Recognition and Intelligent Systems
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In most electronic imaging applications, images with high resolution (HR) are often desired and required. In the process of acquiring the image, there are many factors lead to declines in image quality, such as sports, system noise. At the same time, the limit of imaging device makes the resolution of the image meet the application requirements. It is expensive and difficult to increase the current resolution level by improving hardware performance. Therefore, super-resolution image reconstruction is an effective way to improve the spatial resolution of the image.Super-Resolution (SR) Image Reconstruction is the technology of reconstructing a frame of image with high resolution from a group of warped, blurred and noised Low-Resolution (LR) Images or video sequence about the same scene. It mainly integrates the relative movement information of the same scene's multiple low-resolution into the single high-resolution image, and obtains a high-quality image.This thesis studies the two key issues of the reconstruction process on the basis of the mechanism of degraded image, image registration and reconstruction algorithm.For the basic part of super-resolution image reconstruction, image registration, in order to the accurate registration, the thesis describes and contrast two registration methods, namely, Taylor series method and phase related to template matching. Focusing on the displacement directions of the phase correlation method, the thesis makes provision of the directional shift so as to get the correct amount of displacement.According to the different theoretical system, the thesis discusses and realizes the three airspace commonly kinds of image reconstruction method. In the Maximum a Posteriori (MAP) method, by the relationship between the displacements of low-resolution sequence, construct degraded matrix of every point of low-resolution images using Gaussian function, as well as do a specific analysis about the regularization parameter. With the ringing effect of high-resolution reconstruction image based on the Projection onto Convex Sets (POCS) algorithm included, this thesis proposes a trapezoidal filtering method. The experimental tests show that this algorithm can significantly improve the quality of the reconstruction image. Finally Make understand and do the experiments about the reconstruction based on normal convolution (NC).
Keywords/Search Tags:Super-resolution, Image registration, Maximum a Posteriori, Projection onto Convex Set, Normal convolution
PDF Full Text Request
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