Abstract
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,A MATLAB implementation of the system is available online at http:// www.cns.nyu.edu/lcv/qaware. 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.
Original language | English (US) |
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Pages (from-to) | 1680-1689 |
Number of pages | 10 |
Journal | IEEE Transactions on Image Processing |
Volume | 15 |
Issue number | 6 |
DOIs | |
State | Published - Jun 2006 |
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
ASJC Scopus subject areas
- Software
- Computer Graphics and Computer-Aided Design