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Journal ArticleDOI

Blind noisy image quality assessment using block homogeneity

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TLDR
Experimental results are provided to demonstrate that the proposed image noise estimation approach yields superior accuracy and stability performance to that of conventional approaches, and the proposedimage quality assessment approach achieves consistent performance to the that of human subjective evaluation.
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This article is published in Computers & Electrical Engineering.The article was published on 2014-04-01. It has received 18 citations till now. The article focuses on the topics: Image quality & Image noise.

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Citations
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Journal ArticleDOI

No-reference image quality assessment algorithms: A survey

TL;DR: A survey of existing algorithms for no-reference image quality assessment is presented, which includes type of noise and distortions covered, techniques and parameters used by these algorithms, databases on which the algorithms are validated and benchmarking of their performance with each other and also with human visual system.
Journal ArticleDOI

Local gradient patterns (LGP): An effective local-statistical-feature extraction scheme for no-reference image quality assessment

TL;DR: The results confirm that the proposed LGP metric provides predictive performance that is superior to most state-of-the-art NR-IQA metrics and has an acceptable level of computational complexity.
Journal ArticleDOI

Novel FPGA-based Methodology for Early Broken Rotor Bar Detection and Classification Through Homogeneity Estimation

TL;DR: Results demonstrate the high efficiency of the proposed methodology as a deterministic technique for incipient BRB diagnosis in induction motors, which can detect and differentiate among half, one, or two BRBs with a certainty greater than 99.7%.
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No-reference/blind image quality assessment: a survey

TL;DR: This paper comprehensively review the fundamental developments of NR-IQA with more emphasis on general-purpose NR- IQA algorithms, focusing on the two major aspects of features extraction and quality prediction.
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Fast and reliable noise level estimation based on local statistic

TL;DR: Analysis of the distribution of local variance shows that when local variances are not greater than the threshold that satisfies a special condition, their average is always linearly correlated with the real noise variance, thus the actual noise variance can be obtained from these patches.
References
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Journal ArticleDOI

A model of saliency-based visual attention for rapid scene analysis

TL;DR: In this article, a visual attention system inspired by the behavior and the neuronal architecture of the early primate visual system is presented, where multiscale image features are combined into a single topographical saliency map.

A model of saliency-based visual attention for rapid scene analysis

Laurent Itti
TL;DR: A visual attention system, inspired by the behavior and the neuronal architecture of the early primate visual system, is presented, which breaks down the complex problem of scene understanding by rapidly selecting conspicuous locations to be analyzed in detail.
Journal ArticleDOI

FSIM: A Feature Similarity Index for Image Quality Assessment

TL;DR: A novel feature similarity (FSIM) index for full reference IQA is proposed based on the fact that human visual system (HVS) understands an image mainly according to its low-level features.
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Total variation blind deconvolution

TL;DR: A blind deconvolution algorithm based on the total variational (TV) minimization method proposed is presented, and it is remarked that psf's without sharp edges, e.g., Gaussian blur, can also be identified through the TV approach.
Journal ArticleDOI

A Two-Step Framework for Constructing Blind Image Quality Indices

TL;DR: A new two-step framework for no-reference image quality assessment based on natural scene statistics (NSS) is proposed, which does not require any knowledge of the distorting process and the framework is modular in that it can be extended to any number of distortions.
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