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No-Reference Image Quality Assessment and Blind Deblurring with Sharpness Metrics Exploiting Fourier Phase Information
It has been known for more than 30 years that most of the geometric content of a digital image is encoded in the phase of its Fourier transform. This has led to several works that exploit the global (Fourier) or local (Wavelet) phase information of an image to achieve quality assessment, edge detect...
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Published in: | Journal of mathematical imaging and vision 2015-05, Vol.52 (1), p.145-172 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | It has been known for more than 30 years that most of the geometric content of a digital image is encoded in the phase of its Fourier transform. This has led to several works that exploit the global (Fourier) or local (Wavelet) phase information of an image to achieve quality assessment, edge detection, and, more recently, blind deblurring. We here propose a deeper insight into three recent sharpness metrics (global phase coherence, sharpness index, and a simplified version of it), which all measure in a probabilistic sense the surprisingly small total variation of an image compared to that of certain associated random phase fields. We exhibit several theoretical connections between these indices and study their behavior on a general class of stationary random fields. We also use experiments to highlight the behavior of these metrics with respect to blur, noise, and deconvolution artifacts (ringing). Finally, we propose an application to isotropic blind deblurring and illustrate its efficiency on several examples. |
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ISSN: | 0924-9907 1573-7683 |
DOI: | 10.1007/s10851-015-0560-5 |