Popularity of watermarking is increasing day by day due to the significance of copyright protection, broadcast monitoring, content authentication and many other applications. This paper introduces a novel Discrete Wavelet Transform (DWT) -Singular Value Decomposition (SVD) based watermarking technique to improve the robustness and imperceptibility. In this approach watermark images are hided into the intermediate frequency bands of the cover image by modifying the singular values. The technique has been verified under the presence of attacks like Gaussian blur, Gaussian noise, Salt and pepper noise and Speckle noise. Simulation results of the proposed algorithm shows that it has high robustness against various attacks.
The progress in computer network technology, processing, reproducing and distribution of digital images has becomes very easy. Apart from its advantages, it also gives an opportunity to the attacker or illegal user. Two major approaches available to protect digital images are watermarking technique and encryption technique. This paper presents a combined watermarking and encryption method to further improve the security of the images. It uses Discrete Wavelet Transform (DWT)-Singular Value Decomposition (SVD) watermarking technique and chaotic encryption method. After embedding the two watermark images into the host image it is encrypted and transmitted. At the receiver side it is decrypted and the watermarks are recovered. Simulation results prove that the proposed method is simple and more secure.
This paper presents a new approach of edge preserving and edge based segmentation for compression of images using Modified Fast Haar wavelet transform (MFHW) and Bit Plane Encoder to elevate the compression ratio with high picture quality. The edges of an image are preserved to increase the PSNR, and then the detected edges are used to segment the foreground and background images. The Foreground of the image is given more importance than the background images. A wavelet transform is used to extract the redundant information at low frequency and a matching Bit Plane encoder is used to code the segments of the image at different quality levels. The Proposed method highly preserves quality of the foreground image. Normal compression algorithms will not preserve the high frequency details such as edges, corners etc., in this method edges are preserved and used for segmenting the layers of the original image. The two level Fast haar Wavelet transform is used to decompose the image at different frequency levels, which has high multi-resolution characteristics. The proposed method increases both the compression ratio and PSNR.
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