Singular Value Decomposition Based Image Steganography Using Integer Wavelet Transform

Transform domain Steganography techniques embed secret message in significant areas of cover image. These techniques are generally more robust against common image processing operations. In this paper, we propose an image Steganography method using singular value decomposition (SVD) and integer wavelet transform (IWT). SVD and IWT strengthen the performance of image Steganography and improve the perceptual quality of Stego images. Results have been taken over standard image data sets and compared with discrete cosine transform (DCT) and redundant discrete wavelet transform (RDWT) based image Steganography methods using peak signal to noise ratio (PSNR) correlation coefficients (CC) metrics. Experimental results show that the proposed SVD and IWT based method provides more robustness against image processing and geometric attacks, such as JPEG compression, low-pass filtering, median filtering, and addition of noise, scaling, rotation, and histogram equalization.