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Image information hiding technology can embed more data without increasing the amount of transmitted data. But in most cases, the information embedding rate is different for different carrier images. To increase the embedding rate, the data will be damaged. In order to improve this problem, a new near-lossless image information hiding algorithm with controlled hiding capacity is proposed, which is referred to as NLH. This method makes the pre-processed data in a specific range to facilitate information hiding by interval transformation and data mapping. According to analysis and calculation, the lossless performance of the proposed algorithm in this paper is better than the LSB algorithm. And the result of simulation shows that this method has a fixed information embedding rate (18.75%/1.5bpp) without more transmitted data, and the original image is restored losslessly or nearly losslessly with the improved transmission efficiency.

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Preserving the information of multi-focus source images was neglected in previous image fusion schemes since source image data discarding will happen during the fusion process. Data hiding technology can utilize the redundant bits to embed essential secret data. Inspired from that we proposed a multi-focus image reconstruction algorithm using adaptive regional data hiding. Integrating the Human Visual System (HVS) into the reconstruction module, we further proposed a visual grayscale information entropy operator, which is implemented to segment fused images into texture and flat regions for adaptive data hiding after unfocused region data compression. Our method achieves excellent performances in reconstruction Peak signal-to-noise Ratio (PSNR) above 43dB and maintains the satisfying visual effect of the fused images.