Secret image scrambling and DWT-based image steganography using smoothing operation and convolution neural networks

Steganography is known as a secret data sharing technique. It is a method of data protection which allows the user to send the information in enveloped form. That means the hidden data cannot be seen by the observer because one can only see the enveloped media. This paper presents a steganography technique using Pixel swapping-Quantum Hilbert image scrambling and discrete wavelet transformation, followed by stego image smoothing operation. Initial steps of proposed image steganography include best suitable cover image selection for secret image. This process compares the secret image with the different cover image presents in senders cover image database. Before embedding (encoding), the secret image is scrambled, and then performs the DWT transformation on this scrambled image and cover image. Next steps embed both resultant images and generate a new image named as stego image. The picture quality of stego image is increased using pixel swapping based operation. The Decoding process of proposed steganography scheme is just reverse of the former encoding process followed by application of Convolutional neural networks (CNN) to improve the extracted secret image quality. The results show the strength of the proposed technique.