Dual images in reversible data hiding with adaptive color space variation using wavelet transforms

PurposeSteganography is a data hiding technique used in the data security. while transmission of data through channel, no guarantee that the data is transmitted safely or not. Variety of data security techniques exists such as patch work, low bit rate data hiding, lossy compression etc. This paper aims to increase the security and robustness.Design/methodology/approachThis paper describes, an approach for multiple images steganography that is oriented on the combination of lifting wavelet transform (LWT) and discrete cosine transform (DCT). Here, we have one cover image and two secret images. The cover image is applied with one of the different noises like Gaussian, Salt & Pepper, Poisson, and speckle noises and converted into different color spaces of YCbCr, HSV, and Lab.FindingsDue to the vast development of Internet access and multimedia technology, it becomes very simple to hack and trace secret information. Using this steganography process in reversible data hiding (RDH) helps to prevent secret information.Originality/valueWe can divide the color space converted image into four sub-bands of images by using lifting wavelet transform. By selecting lower bands, the discrete cosine transform is computed for hiding two secret images into the cover image and again one of the transformed secret images is converted by using Arnold transform to get the encrypted/embedded/encoded image. To extract the Stego image, we can apply the revertible operation. For comparing the results, we can calculate PSNR, SSIM, and MSE values by applying the same process for all color spaces of YCbCr, HSV, and Lab. The experimental results give better performance when compared to all other spaces.

A Novel Approach based on Lifting Wavelet Transform for MIMO-OFDM Systems

In this article, two methods are proposed to further increase the advantages of MIMO-OFDM systems such as high access quality, high data rates and spectral efficiency. The first of these is the combination of the MIMO-OFDM system with the fast Walsh Hadamard transform (FWHT) due to its high accomplishment with the ability to spread the data versus the disturbing influences of the channel. The second is the combination of Lifting wavelet transform (LWT), due to its superior advantages such as good time-frequency localization properties, ICI and ISI suppression capabilities due to its orthonormal structure, unlike fast Fourier transform (FFT), with MIMO-OFDM scheme. Computer simulation studies are carried out to verify the accomplishment of the suggested methods over the bit error rate (BER) and peak to average power ratio (PAPR) benchmark. From the acquired outcomes, it is noticed that approximately 6 dB of SNR gain and approximately 2 dB of PAPR gain are achieved with the proposed method.

Image Authentication Using Block Truncation Coding in Lifting Wavelet Domain

Image watermarking is one of the most accepted solutions protecting image authenticity. The method presented in this paper not only provides the desired outcome also efficient in terms of memory requirements and preserving image characteristics. This scheme effectively utilizes the concepts of block truncation coding (BTC) and lifting wavelet transform (LWT). The BTC method is applied to observe the binary watermark image corresponding to its gray-scale image. Whereas, the LWT is incorporated to transform the cover image from spatial coordinates to corresponding transform coordinates. In this, a quantization-based approach for watermark bit embedding is applied. And, the extraction of binary watermark data from the attacked watermarked image is based on adaptive thresholding. To show the effectiveness of the proposed scheme, the experiment over different benchmark images is performed. The experimental results and the comparison with state-of-the-art schemes depict not only the good imperceptibility but also high robustness against various attacks.

Data hiding in encryption–compression domain

This paper introduces a robust and secure data hiding scheme to transmit grayscale image in encryption-then-compression domain. First, host image is transformed using lifting wavelet transform, Hessenberg decomposition and redundant singular value decomposition. Then, we use appropriate scaling factor to invisibly embed the singular value of watermark data into the lower frequency sub-band of the host image. We also use suitable encryption-then-compression scheme to improve the security of the image. Additionally, de-noising convolutional neural network is performed at extracted mark data to enhance the robustness of the scheme. Experimental results verify the effectiveness of our scheme, including embedding capacity, robustness, invisibility, and security. Further, it is established that our scheme has a better ability to recover concealed mark than conventional ones at low cost.