No-reference visually significant blocking artifact metric for natural scene images
- UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
- Shanmugatha "Shan" Suthaharan, Associate Professor (Creator)
- Institution
- The University of North Carolina at Greensboro (UNCG )
- Web Site: http://library.uncg.edu/
Abstract: Quantifying visually annoying blocking artifacts is essential for image and video quality assessment. This paper presents a no-reference technique that uses the multi neural channels aspect of human visual system (HVS) to quantify visual impairment by altering the outputs of these sensory channels independently using statistical “standard score” formula in the Fourier domain. It also uses the bit patterns of the least significant bits
(LSB) to extract blocking artifacts. Simulation results show that the blocking artifact extracted using this approach follows subjective visual interpretation of blocking artifacts. This paper also presents a visually significant blocking artifact metric (VSBAM) along with some experimental results.
No-reference visually significant blocking artifact metric for natural scene images
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Created on 3/11/2011
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Additional Information
- Publication
- Signal Processing 89, pp. 1647-1652.
- Language: English
- Date: 2009
- Keywords
- Natural scene images, JPEG compression, Neural channels, Blocking artifacts