No-reference quality assessment using natural scene statistics: JPEG2000

Measurement of image or video quality is crucial for many image-processing algorithms, such as acquisition, compression, restoration, enhancement, and reproduction. Traditionally, image quality assessment (QA) algorithms interpret image quality as similarity with a "reference" or "per...

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Bibliographic Details
Published in:	IEEE transactions on image processing Vol. 14; no. 11; pp. 1918 - 1927
Main Authors:	Sheikh, H.R., Bovik, A.C., Cormack, L.
Format:	Journal Article
Language:	English
Published:	New York, NY IEEE 01.11.2005 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Applied sciences Blind quality assessment (QA) Computer Simulation Detection, estimation, filtering, equalization, prediction Distortion measurement Exact sciences and technology Humans Image coding Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image processing image QA Image quality Image restoration Information Storage and Retrieval - methods Information, signal and communications theory JPEG2000 Layout Models, Statistical natural scene statistics (NSS) no reference (NR) image QA Quality assessment Quality Control Signal and communications theory Signal processing Signal Processing, Computer-Assisted Signal, noise Statistics Subtraction Technique Telecommunications and information theory Transform coding Video compression Video Recording - methods Video coding JPEG2000 Blocking artifact Similarity Image processing Data compression Image compression Algorithm Blurred image Subjective evaluation Video signal processing natural scene statistics (NSS) Image quality no reference (NR) image QA Image coding Wavelet transformation Quality control image QA Signal processing Blind quality assessment (QA) Image evaluation
ISSN:	1057-7149, 1941-0042
Online Access:	Get full text
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