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No reference image blur estimation

Author: ZhuHongLiang
Tutor: ZhangRong
School: University of Science and Technology of China
Course: Signal and Information Processing
Keywords: Image Quality Assessment Ambiguity Estimation Template matching Line spread function Significant area
CLC: TP391.41
Type: Master's thesis
Year: 2010
Downloads: 189
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Abstract


The visual information is the main way of human access information, which is acquired by the person's own visual perception system, wherein the image information is the most important part. With the development of the personal computer, digital communications, multimedia and network technology, digital images and digital video is increasingly becoming one of the most important carrier of information, has penetrated into people's daily lives, and spread to millions of households. In every step of the digital image acquisition, processing, encoding, storage, transmission and reconstruction, usually have an impact on the quality of the image and how to evaluate the image quality of the image processing and computer vision field of basic and challenging problems. In this thesis, no reference image quality assessment is an important part - the reference image blur estimation. Distortion characteristics in the study of image blur, fuzzy process modeling, edge information extraction, HVS system significantly with the sexual characteristics of the basis, is proposed based on template matching no reference image fuzzy degree estimated method and based on the vision significantly with sexual weighted the image fuzzy degree The estimation method. This thesis mainly focus on the analysis of the type of image edge the Gaussian template matching and visual significant sexual characteristics and key technology research work. Work and innovations are summarized as follows: 1) template matching method for image ambiguity estimation is proposed based on template matching image blur estimation method. Design the adaptive fracture edge connector optimized for edge detection. Set of templates, create a Gaussian the gradient profile curve with the edge of the template set template template matching, calculate the standard deviation of the edge gradient in the case of the best signal-to-noise ratio. Through all the edge gradient profile curve of the standard deviation of the distributed computing image global ambiguity. The principle of the template matching method is a matched filter, matched filter having the advantages of the maximum signal-to-noise ratio signal detection. The template in the template set as a signal, the edge gradient of the contour curve as the filter, the output of the filter is the best matching template, as the edge gradient of the standard deviation of the contour curve with a standard deviation of the best matching template. 2) The image significantly theory applied to the estimation of the image blur degree, and to optimize the degree of image blur estimation result, so that the the estimated image blur degree and subjective blur degree having a higher linearity between. Image significantly refers HVS when viewing an image, the viewpoint is always concentrated in some meaningful area, in general, these meaningful regional structural obvious area, this paper introduces the multi-scale significant The region extraction optimize extraction algorithm based multi-scale image a significant area.

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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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