Image Quality Assessment with Degradation on Spatial Structure

In this letter, we introduce an improved structural degradation based image quality assessment (IQA) method. Most of the existing structural similarity based IQA metrics mainly consider the spatial contrast degradation but have not fully considered the changes on the spatial distribution of structur...

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Bibliographic Details
Published in:IEEE signal processing letters 2014-04, Vol.21 (4), p.437-440
Main Authors: Wu, Jinjian, Lin, Weisi, Shi, Guangming
Format: Article
Language:English
Subjects:
Assessments
Degradation
Distortion
Distortion measurement
Distribution functions
Fish
Graphical models
Image edge detection
Image quality
Image quality assessment
local binary patterns
Mathematical analysis
Perception
Similarity
Spatial distribution
structural degradation
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Summary:In this letter, we introduce an improved structural degradation based image quality assessment (IQA) method. Most of the existing structural similarity based IQA metrics mainly consider the spatial contrast degradation but have not fully considered the changes on the spatial distribution of structures. Since the human visual system (HVS) is sensitive to degradations on both spatial contrast and spatial distribution, both factors need to be considered for IQA. In order to measure the structural degradation on spatial distribution, the local binary patterns (LBPs) are first employed to extract structural information. And then, the LBP shift between the reference and distorted images is computed, because noise distorts structural patterns. Finally, the spatial contrast degradation on each pair of LBP shifts is calculated for quality assessment. Experimental results on three large benchmark databases confirm that the proposed IQA method is highly consistent with the subjective perception.
ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2014.2304714