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Study on Ownership Identification Using Discrete Wavelet Transform (DWT)-Based LOGO Watermarking

Authors: T. Mita Kumari; Gayadhar Panda;

Study on Ownership Identification Using Discrete Wavelet Transform (DWT)-Based LOGO Watermarking

Abstract

An efficient DWT-based watermarking technique is proposed in this research to insert gray-scale logos as a watermark in images to attest the owner identify and discourage unauthorised copying. To hide a higher energy hidden watermark in conspicuous picture components, the method converts both the host image and the watermark into the discrete wavelet domain, where their coefficients are fused adaptively based on the Human Visual System (HVS) model. The method merges the watermark coefficients at various resolution levels of the host image, resulting in simultaneous spatial localisation and frequency spread of the watermark, as well as robustness against various attacks. According to the simulation results, the suggested method is robust to a wide range of attacks, including image compression, linear and non-linear filtering, noise addition, image resizing, cropping, and enhancement, among others.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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