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Minimisation of image watermarking side effects through subjective optimisation

Golestani, Hossein Bakhshi and Ghanbari, Mohammed (2013) 'Minimisation of image watermarking side effects through subjective optimisation.' IET Image Processing, 7 (8). pp. 733-741. ISSN 1751-9659

1501.01755v1.pdf - Accepted Version

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This study investigates the use of structural similarity index (SSIM) on the minimised side effect to image watermarking. For the fast implementation and more compatibility with the standard discrete cosine transform (DCT)-based codecs, watermark insertion is carried out on the DCT coefficients and hence an SSIM model for DCT-based watermarking is developed. For faster implementation, the SSIM index is maximised over independent 4 × 4 non-overlapped blocks, but the disparity between the adjacent blocks reduces the overall image quality. This problem is resolved through optimisation of overlapped blocks, but, the higher image quality is achieved at a cost of high computational complexity. To reduce the computational complexity while preserving the good quality, optimisation of semi-overlapped blocks is introduced. The authors show that while SSIM-based optimisation over overlapped blocks has as high as 64 times the complexity of the 4 × 4 non-overlapped method, with semi-overlapped optimisation the high quality of overlapped method is preserved only at a cost of less than 8 times the non-overlapped method.

Item Type: Article
Additional Information: 17 pages,11 figures, IET Image Processing Journal
Uncontrolled Keywords: computational complexity; discrete cosine transforms; minimisation; image watermarking; image watermarking side effect minimisation; subjective optimisation; structural similarity index; standard DCT-based codecs; watermark insertion; DCT coefficients; SSIM model; independent nonoverlapped blocks; image quality reduction; computational complexity reduction; semioverlapped block optimisation
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 08 Jul 2019 14:32
Last Modified: 06 Jan 2022 13:49

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