This paper presents a novel image hiding method with improved block matching way and high embedding capacity that allows the important image (IM) to be several times larger than the cover image. Multi-layered least-significant-bit (LSB) planes of the cover image (CI) are obtained for constructing the candidate block-matching set (CBMS) by using the features fusion which consists of the texture features of wavelet transform and gray level difference; By combining features way to search the best-matching blocks from the CBMS, and the Huffman coding is used to compress the data including the indices of the best-matching blocks, the not-well-matched blocks part of IM and the parameters into a secret information flow which is embedded into the double-layered bit planes of CI by using a high embedding rate encoder. Because the high embedding payload we need, the SPAM features will be chosen to test the performance of resisting steganalysis attack which can obviously improve the security of the stego images.INDEX TERMS block matching way, high embedding capacity, the features fusion, wavelet transform, the double-layer LSB planes, SPAM features
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.