Reduced-Reference Quality Assessment for JPEG-2000 Compressed Image

Ha-Joong PARK  Ho-Youl JUNG  

Publication
IEICE TRANSACTIONS on Communications   Vol.E91-B   No.5   pp.1287-1294
Publication Date: 2008/05/01
Online ISSN: 1745-1345
DOI: 10.1093/ietcom/e91-b.5.1287
Print ISSN: 0916-8516
Type of Manuscript: Special Section PAPER (Special Section on Communication Quality)
Category: Subjective and Objective Assessments of Audio and Video Media Quality
Keyword: 
quality assessment,  JPEG-2000,  reduced-reference,  context information,  noisy channel,  

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Summary: 
Image quality assessment method is a methodology that measures the difference of quality between the reference image and its distorted one. In this paper, we propose a novel reduced-reference (RR) quality assessment method for JPEG-2000 compressed images, which exploits the statistical characteristics of context information extracted through partial entropy decoding or decoding. These statistical features obtained in the process of JPEG-2000 encoding are transmitted to the receiver as side information and used to estimate the quality of images transmitted over various noisy channels at the decompression side. In the framework of JPEG-2000, the context of a current coefficient is determined depending on the pattern of the significance and/or the sign of its neighbors in three bit-plane coding passes and four coding modes. As the context information represents the local property of images, it can efficiently describe textured pattern and edge orientation. The quality of transmitted images is measured by the difference of entropy of context information between received and original images. Moreover, the proposed quality assessment method can directly process the images in the JPEG-2000 compressed domain without full decompression. Therefore, our proposed can accelerate the work of assessing image quality. Through simulations, we demonstrate that our method achieves fairly good performance in terms of the quality measurement accuracy as well as the computational complexity.