No-reference perceptual quality assessment of JPEG compressed images
Zhou Wang
Sheikh, H.R.
Bovik, A.C.
Dept. of Electr. & Comput. Eng., Texas Univ., Austin, TX, USA;
This paper appears in: Image Processing. 2002. Proceedings. 2002 International Conference on
Publication Date: 2002
Volume: 1,
On page(s): I-477- I-480 vol.1
ISSN: 1522-4880
ISBN: 0-7803-7622-6
INSPEC Accession Number: 7590832
Digital Object Identifier: 10.1109/ICIP.2002.1038064
Current Version Published: 2002-12-10
Abstract
Human observers can easily assess the quality of a distorted image without examining the original image as a reference. By contrast, designing objective No-Reference (NR) quality measurement algorithms is a very difficult task. Currently, NR quality assessment is feasible only when prior knowledge about the types of image distortion is available. This research aims to develop NR quality measurement algorithms for JPEG compressed images. First, we established a JPEG image database and subjective experiments were conducted on the database. We show that Peak Signal-to-Noise Ratio (PSNR), which requires the reference images, is a poor indicator of subjective quality. Therefore, tuning an NR measurement model towards PSNR is not an appropriate approach in designing NR quality metrics. Furthermore, we propose a computational and memory efficient NR quality assessment model for JPEG images. Subjective test results are used to train the model, which achieves good quality prediction performance.
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