Perceptual Quality Metric With Internal Generative Mechanism

Objective image quality assessment (IQA) aims to evaluate image quality consistently with human perception. Most of the existing perceptual IQA metrics cannot accurately represent the degradations from different types of distortion, e.g., existing structural similarity metrics perform well on conten...

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Bibliographic Details
Published in:	IEEE transactions on image processing Vol. 22; no. 1; pp. 43 - 54
Main Authors:	Wu, Jinjian, Lin, Weisi, Shi, Guangming, Liu, Anmin
Format:	Journal Article
Language:	English
Published:	New York, NY IEEE 01.01.2013 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Animals Applied sciences Artificial Intelligence Bayes Theorem Bayesian methods Databases, Factual Degradation Detection, estimation, filtering, equalization, prediction Distortion Exact sciences and technology Human Human visual system Humans image decomposition Image edge detection Image processing Image Processing, Computer-Assisted - methods Image quality image quality assessment (IQA) Information, signal and communications theory internal generative mechanism (IGM) Measurement Models, Theoretical Perception PSNR Signal and communications theory Signal processing Signal, noise Signal-To-Noise Ratio Similarity Studies Telecommunications and information theory Uncertainty Visual Visual Perception Visualization internal generative mechanism (IGM) State of the art Image processing Similarity Image interpretation Objective analysis Autoregressive model Human visual system Algorithm Subjective evaluation Degradation Image quality Image segmentation Residual impurity Quality control Database Metric Visual information image decomposition Damaging Image evaluation Signal to noise ratio image quality assessment (IQA)
ISSN:	1057-7149, 1941-0042, 1941-0042
Online Access:	Get full text
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