|Table of Contents|

[1] Wang Tonghan, Zhang Lu, Jia Huizhen, Kong Youyong, et al. Image quality assessment based on perceptual grouping [J]. Journal of Southeast University (English Edition), 2016, 32 (1): 29-34. [doi:10.3969/j.issn.1003-7985.2016.01.006]
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Image quality assessment based on perceptual grouping()
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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
32
Issue:
2016 1
Page:
29-34
Research Field:
Information and Communication Engineering
Publishing date:
2016-03-20

Info

Title:
Image quality assessment based on perceptual grouping
Author(s):
Wang Tonghan1 Zhang Lu2 Jia Huizhen3 Kong Youyong1 Li Baosheng1 4 Shu Huazhong1
1Laboratory of Image Science and Technology, Southeast University, Nanjing 210096, China
2IETR Lab(UMR CNRS 6164), INSA de Rennes, 20 Avenue des Buttes de Coesmes, CS 70839F-35708 Rennes Cedex 7, France
3School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
4Shandong Cancer Hospital, Jinan 250117, China
Keywords:
perceptual grouping perceptual image quality assessment superpixels full reference
PACS:
TN911.73
DOI:
10.3969/j.issn.1003-7985.2016.01.006
Abstract:
To further explore the human visual system(HVS), the perceptual grouping(PG), which has been proven to play an important role in the HVS, is adopted to design an effective image quality assessment(IQA)model. Compared with the existing fixed-window-based models, the proposed one is an adaptive window-like model that introduces the perceptual grouping strategy into the IQA model. It works as follows: first, it preprocesses the images by clustering similar pixels into a group to the greatest extent; then the structural similarity is used to compute the similarity of the superpixels between reference and distorted images; finally, it integrates all the similarity of superpixels of an image to yield a quality score. Experimental results on three databases(LIVE, IVC and MICT)show that the proposed method yields good performance in terms of correlation with human judgments of visual quality.

References:

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Memo

Memo:
Biographies: Wang Tonghan(1984—), male, graduate; Shu Huazhong(corresponding author), male, doctor, professor, shu.list@seu.edu.cn.
Foundation items: The National Natural Science Foundation of China(No.81272501), the National Basic Research Program of China(973 Program)(No.2011CB707904), Taishan Scholars Program of Shandong Province, China(No. ts20120505).
Citation: Wang Tonghan, Zhang Lu, Jia Huizhen, et al. Image quality assessment based on perceptual grouping[J].Journal of Southeast University(English Edition), 2016, 32(1):29-34. DOI:10.3969/j.issn.1003-7985.2016.01.006.
Last Update: 2016-03-20