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Quality-aware images

delete2006-06-01
delete252
PRE
AI
Z
Zhou Wang *
G
Guixing Wu
H
Hamid R. Sheikh
E
Eero P. Simoncelli
Y
Yang, En-Hui
A
Alan C. Bovik
DOI:10.1109/TIP.2005.864165delete
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Abstract

Abstract

En 中文
We propose the concept of quality-aware image, in which certain extracted features of the original (high-quality) image are embedded into the image data as invisible hidden messages. When a distorted version of such an image is received, users can decode the hidden messages and use them to provide an objective measure of the quality of the distorted image. To demonstrate the idea, we build a practical quality-aware image encoding, decoding and quality analysis system,(1) which employs: 1) a novel reduced-reference image quality assessment algorithm based on a statistical model of natural images and 2) a previously developed quantization watermarking-based data hiding technique in the wavelet transform domain.
Keywords:
Generalized Gaussian density (GGD)
image communication
image quality assessment
image watermarking
information
hiding
natural image statistics
quality-aware image
reduced-reference
image quality assessment
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Transactions on Image Processing cover
IEEE Transactions on Image Processing
IF:
13.7
Papers:
1.0W
Citations:
8.4W

Organization

No organization information available
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