An Efficient Image Steganography Approach Based on Qr Factorization and Singular Value Decomposition in Non-Subsampled Contourlet Transform Domain

Data security is considered a significant issue while doing communication over cyberspace, as the quantity of information shared through the virtual world is expanding exponentially day by day. Steganography can play an integral part in safe-guarding the data from the unauthorized users through a hiding mechanism. In this study, a three steps robust image steganography algorithm based on QR factorization and singular value decomposition (SVD) in NSCT (Non-subsampled contourlet transform) domain is described. First, this algorithm scrambles the secret image using Arnold transforms and then NSCT decomposes the carrier and the scrambled secret image into non-subsampled contourlet coefficients. Second, the QR factorization and SVD are used on the specific coefficients of carrier and scrambled secret images, respectively. Finally, the modified secret image inserts into the carrier image to produce the image of stego for communication. At the receiving end, the reverse mechanism is applied to discover the hidden message. The methodology gives superior imperceptibility as well as robustness. Besides, the effectiveness of the planned approach is compared with the ongoing methods