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Research On Fuzzy Image Restoration And Correction Method

Posted on:2009-04-28Degree:MasterType:Thesis
Country:ChinaCandidate:M Q ZhangFull Text:PDF
GTID:2178360272479400Subject:Control Engineering
Abstract/Summary:PDF Full Text Request
With the development of society's productivity, image processing technology has already far broken through the early application, widely applied to a lot of fields, such as scientific research, industrial and agricultural production, military technology, government department, health care, etc. The image processing technology includes various kinds of processing, for example, carrying on the digitization, coding, analyzing to the image etc. Certainly the degraded image processing is a very important research field in digital image processing, its research results are being widely applied to each field stated above.In this paper, the methods for blind restoration of turbulence-degraded images caused by aero-optics effects are mainly discussed, containing:1. The background and purport of research for the restoration of image are introduced. And the development of the restoration methods is summarized.2. The methods of Least Squares and the expectation-maximum(EM) based on the ARMA image model are introduced, especially the efficient NNLS method in the paper.3. The main problems in blind restoration, including noise amplification and ringing effect, and the tradeoff between them -regularization, are analyzed. Then some widely used methods for blind restoration are introduced here.4. The evaluation methods of restoration is deeply summarized. In the interest of human vision on the basis of, a human visual interest based on the characteristics of image quality objective evaluation method to solve the traditional method of objective evaluation of subjective evaluation methods and contradictory issues, but also such methods Only in the initial stage, there are still many problems to be solved.
Keywords/Search Tags:Image restoration, Least squares, Taylor series, The ringing effects
PDF Full Text Request
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