LAUSR

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.