Content-adaptive reliable robust lossless data embedding
Neurocomputing
Efficient reversible data hiding for color filter array images
Information Sciences: an International Journal
Intelligent reversible watermarking and authentication: Hiding depth map information for 3D cameras
Information Sciences: an International Journal
Graph matching with geometric constraints for near-duplicated image retrieval
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
Secret sharing with multi-cover adaptive steganography
Information Sciences: an International Journal
Information Sciences: an International Journal
Reversible data hiding for depth maps using the depth no-synthesis-error model
Information Sciences: an International Journal
Hi-index | 0.00 |
Histogram-based lossless data embedding (LDE) has been recognized as an effective and efficient way for copyright protection of multimedia. Recently, a LDE method using the statistical quantity histogram has achieved good performance, which utilizes the similarity of the arithmetic average of difference histogram (AADH) to reduce the diversity of images and ensure the stable performance of LDE. However, this method is strongly dependent on some assumptions, which limits its applications in practice. In addition, the capacities of the images with the flat AADH, e.g., texture images, are a little bit low. For this purpose, we develop a novel framework for LDE by incorporating the merits from the generalized statistical quantity histogram (GSQH) and the histogram-based embedding. Algorithmically, we design the GSQH driven LDE framework carefully so that it: (1) utilizes the similarity and sparsity of GSQH to construct an efficient embedding carrier, leading to a general and stable framework; (2) is widely adaptable for different kinds of images, due to the usage of the divide-and-conquer strategy; (3) is scalable for different capacity requirements and avoids the capacity problems caused by the flat histogram distribution; (4) is conditionally robust against JPEG compression under a suitable scale factor; and (5) is secure for copyright protection because of the safe storage and transmission of side information. Thorough experiments over three kinds of images demonstrate the effectiveness of the proposed framework.