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Digital Video Watermarking based on Different Wavelet Transform

Dhanashree S. Shedge, Aarti G. Ambekar. Published in Image Processing.

Communications on Applied Electronics
Year of Publication: 2016
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Dhanashree S. Shedge, Aarti G. Ambekar

Dhanashree S Shedge and Aarti G Ambekar. Digital Video Watermarking based on Different Wavelet Transform. Communications on Applied Electronics 5(10):37-41, September 2016. BibTeX

	author = {Dhanashree S. Shedge and Aarti G. Ambekar},
	title = {Digital Video Watermarking based on Different Wavelet Transform},
	journal = {Communications on Applied Electronics},
	issue_date = {September 2016},
	volume = {5},
	number = {10},
	month = {Sep},
	year = {2016},
	issn = {2394-4714},
	pages = {37-41},
	numpages = {5},
	url = {},
	doi = {10.5120/cae2016652387},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


In one's everyday life, web is developing and turned into an imperative part. Digital content can easily be downloaded, duplicated or altered. Digital content can be secured by number of ways. Digital Watermarking is one of the strategies for the insurance of Digital Content. Digital Watermarking is a plan of copyright protection in which a watermark data is embedded into cover image in such a way that the watermark data is not detected and it is invisible. A watermark will be an intellectual property rights is in the form of image, audio, text, numbers etc emerged into images, video files, audio files and other multimedia data having assured methods, approaches, algorithms. To protect the authentication and authorization rights, different wavelet transform based techniques have been proposed to making the watermarked data more robust, imperceptible and secure. In this work, watermarking has been done using SVD method, and comparison of Discrete wavelet transform (DWT) and Lifting wavelet transform(LWT). The results of the scheme are compared the imperceptibility and the robustness of the video frame, on the basis of the parameters such as, correlation coefficient (CC), peak signal to noise ratio (PSNR) and structural similarity index (SSIM ).


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Discrete Wavelet Transform, Lifting Wavelet Transform, Singular Value Decomposition, Copyright Protection.