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Singular Values Decomposition and Lifting Wavelet Transform for Speech Signal Embedding into Digital Image

[ Vol. 12 , Issue. 2 ]

Author(s):

Mourad Talbi* and Mohammed Salim Bouhlel   Pages 131 - 142 ( 12 )

Abstract:


Background: In this paper, we propose a secure image watermarking technique which is applied to grayscale and color images. It consists in applying the SVD (Singular Value Decomposition) in the Lifting Wavelet Transform domain for embedding a speech image (the watermark) into the host image.

Methods: It also uses signature in the embedding and extraction steps. Its performance is justified by the computation of PSNR (Pick Signal to Noise Ratio), SSIM (Structural Similarity), SNR (Signal to Noise Ratio), SegSNR (Segmental SNR) and PESQ (Perceptual Evaluation Speech Quality).

Results: The PSNR and SSIM are used for evaluating the perceptual quality of the watermarked image compared to the original image. The SNR, SegSNR and PESQ are used for evaluating the perceptual quality of the reconstructed or extracted speech signal compared to the original speech signal.

Conclusion: The Results obtained from computation of PSNR, SSIM, SNR, SegSNR and PESQ show the performance of the proposed technique.

Keywords:

Speech image, color image, grayscale image, singular values decomposition, lifting wavelet transform, image watermarking, watermark, secure.

Affiliation:

Center of Researches and Technologies of Energy of Borj Cedria, Tunis, Sciences Electroniques, Technologie de l`Information et Telecommunications (SETIT)



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