A Cover-Independent Deep Image Hiding Method Based on Domain Attention Mechanism

Recently,deep image-hiding techniques have attracted considerable attention in covert communication and high-capacity information hiding.However,these approaches have some limitations.For example,a cover image lacks self-adaptability,information leakage,or weak concealment.To address these issues,this study proposes a universal and adaptable image-hiding method.First,a domain attention mechanism is designed by combining the Atrous convolution,which makes better use of the relationship between the secret image domain and the cover image domain.Second,to improve perceived human similarity,perceptual loss is incorporated into the training process.The experimental results are promising,with the proposed method achieving an average pixel discrepancy(APD)of 1.83 and a peak signal-to-noise ratio(PSNR)value of 40.72 dB between the cover and stego images,indicative of its high-quality output.Furthermore,the structural similarity index measure(SSIM)reaches 0.985 while the learned perceptual image patch similarity(LPIPS)remarkably registers at 0.0001.Moreover,self-testing and cross-experiments demonstrate the model’s adaptability and generalization in unknown hidden spaces,making it suitable for diverse computer vision tasks.

An Image Encryption Method Based on Bit Plane Hiding Technology

A novel image hiding method based on the correlation analysis of bit plane is described in this paper. Firstly, based on the correlation analysis, different bit plane of a secret image is hided in different bit plane of several different open images. And then a new hiding image is acquired by a nesting ＂Exclusive-OR＂ operation on those images obtained from the first step. At last, by employing image fusion technique, the final hiding result is achieved. The experimental result shows that the method proposed in this paper is effec rive.

An Efficient Information Hiding Scheme Based on Closest Paired Tree Structure Vector Quantization

Information hiding schemes based on vector quantization （VQ） usually require lengthy VQ encoding and decoding processes. In this paper, we propose an efficient information hiding method based on closest paired tree structure vector quantization （CPTSVQ）. The simulation result shows that the execution time of the proposed scheme is much shorter than that attained by previous approaches.

A Steganography-Based Optical Image Encryption System Using RGB Channel Integration

An optical image encryption system with adaptive steganography using red, green, and blue （RGB） channel integration is proposed. The optical image encryption system employs a double random phase encoding algorithm to encrypt and decrypt color images. The RGB channel in a color image is first integrated into a large grayscale image. Then the integrated image is encrypted by two random phase masks. The secret data is then embedded into the encrypted image with a specific hiding sequence generated by the zero-LSB （least significant bits） sorting technique which is a content-dependent and low distortion data embedding method. Experimental results show that the proposed, method has a good performance in both hiding capacity and decrypted image quality.

An Image Authentication Method by Grouping Most Significant Bits

In 2011, Chan proposed an image authentication method by producing the parity check bits from pixels whose bits have been rearranged. Due to this rearrangement, the value of the most-significant bit of each tampered pixel can be determined according to its parity check bits. With the help of the most-significant bit of the pixel, the pixel can be recovered by selecting two possible （7, 4） Hamming code words. However, if the distance between two Hamming code words is within a certain range, incorrect selection may occur. Chan＇s method added one additional bit to indicate the correct one. It is trivial that this may degrade the quality of the authenticated image. In this paper, we group four most-significant bits into different groups to form a mapping codebook and the mapping codebook is used to produce authentication data instead of the （7, 4） Hamming code book. The experimental results show that the proposed method has a greater ability to recover tampered areas.

Distortion-Free Data Embedding Scheme for High Dynamic Range Images

Distortion-free data embedding is a technique which can assure that not only the secret data is correctly extracted but also the cover media is recovered without any distortion after secret data is extracted completely. Because of these advantages, this technique attracts the attention of many researchers. In this paper, a new distortion-free data embedding scheme for high dynamic range （HDR） images is proposed. By depending on Cartesian product, this scheme can obtain higher embedding capacity while maintaining the exactly identical cover image and stego image when using the tone mapping algorithms. In experimental results, the proposed scheme is superior to Yu et aL＇s scheme in regard to the embedding rate——an average embedding rate of 0.1355 bpp compared with Yn et aL＇s scheme （0.1270 bpp）.

High capacity reversible data hiding in encrypted images based on adaptive quadtree partitioning and MSB prediction

To improve the embedding capacity of reversible data hiding in encrypted images(RDH-EI),a new RDH-EI scheme is proposed based on adaptive quadtree partitioning and most significant bit(MSB)prediction.First,according to the smoothness of the image,the image is partitioned into blocks based on adaptive quadtree partitioning,and then blocks of different sizes are encrypted and scrambled at the block level to resist the analysis of the encrypted images.In the data embedding stage,the adaptive MSB prediction method proposed by Wang and He(2022)is improved by taking the upper-left pixel in the block as the target pixel,to predict other pixels to free up more embedding space.To the best of our knowledge,quadtree partitioning is first applied to RDH-EI.Simulation results show that the proposed method is reversible and separable,and that its average embedding capacity is improved.For gray images with a size of 512×512,the average embedding capacity is increased by 25565 bits.For all smooth images with improved embedding capacity,the average embedding capacity is increased by about 35530 bits.