Adaptive Watermarking and Tree Structure Based Image Quality Estimation
| Autor: | Jiying Zhao, Wa James Tam, Dong Zheng, Filippo Speranza, Sha Wang |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
business.industry
Image quality Computer science Structural similarity ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Watermark Pattern recognition Data_CODINGANDINFORMATIONTHEORY Filter (signal processing) Computer Science Applications Set partitioning in hierarchical trees symbols.namesake Tree (data structure) Tree structure Gaussian noise Distortion Signal Processing Media Technology symbols Artificial intelligence Electrical and Electronic Engineering business Digital watermarking |
| Zdroj: | IEEE Transactions on Multimedia. 16:311-325 |
| ISSN: | 1941-0077 1520-9210 |
| DOI: | 10.1109/tmm.2013.2291658 |
| Popis: | Image quality evaluation is very important. In applications involving signal transmission, the Reduced- or No-Reference quality metrics are generally more practical than the Full-Reference metrics. In this study, we propose a quality estimation method based on a novel semi-fragile and adaptive watermarking scheme. The proposed scheme uses the embedded watermark to estimate the degradation of cover image under different distortions. The watermarking process is implemented in DWT domain of the cover image. The correlated DWT coefficients across the DWT subbands are categorized into Set Partitioning in Hierarchical Trees (SPIHT). Those SPHIT trees are further decomposed into a set of bitplanes. The watermark is embedded into the selected bitplanes of the selected DWT coefficients of the selected tree without causing significant fidelity loss to the cover image. The accuracy of the quality estimation is made to approach that of Full-Reference metrics by referring to an "Ideal Mapping Curve" computed a priori. The experimental results show that the proposed scheme can estimate image quality in terms of PSNR, wPSNR, JND and SSIM with high accuracy under JPEG compression, JPEG2000 compression, Gaussian low-pass filtering and Gaussian noise distortion. The results also show that the proposed scheme has good computational efficiency for practical applications. |
| Databáze: | OpenAIRE |
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