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Histogram modelling-based no reference blur quality measure
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DOI：10.1016/j.image.2017.08.014.png)
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Blurring is a common artefact detrimental to the image quality. It affects especially edges and texture features that represent high frequency components of an image. The purpose of this paper is to propose a simple, fast, and faithful measure able to blindly assess blur amount in images. The main idea turns on analysing the frequency response at the multiresolution transitions. To achieve that, the histogram of the discrete cosine transform coefficients of the edge map is modelled by using an exponential probability density function (pd f). Tests revealed that the steepness of the pd f depends on the blur amount, hence, it is used as a cue to characterize the blur effect. Comprehensive testing demonstrates good consistency of the proposed measure with subjective quality scores as well as satisfactory performance when compared with representative state-of-the-art blind blur quality measures. (C) 2017 Elsevier B.V. All rights reserved.
Keyword:
Blind image quality
Blur
High frequencies analysis
Histogram
probability density function
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A No-Reference Objective Image Sharpness Metric Based on the Notion of Just Noticeable Blur (JNB)
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