| Summary: | 碩士 === 國立屏東教育大學 === 資訊科學系 === 97 === In this thesis, a reversible data hiding scheme is proposed for medical images. First, a preprocessing step is performed in the original image to eliminate the pixels with a gray-level of 0 and 255. Then, three prediction methods are employed to estimate the predictive values of the current pixel. The first prediction scheme is based on the median edge detection predictor which used by Hong et al., the second prediction scheme is based on the Lagrange
interpolation, and the third scheme is based on causal weighted average. The difference between the predicted pixel value and the original pixel value is calculated, and the histogram for the prediction error is generated as well. In the histogram, two peak points and two zero points are searched. The number of bits that can be embedded into an image equals to the number of pixels which are associated with the two peak points. In this thesis, many medical images are used for testing. Experimental results show that the proposed method provides a higher pure payload compared with Ni et al.’s method, and the stego-images have good visual image quality.
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