High Capacity Reversible Information Hiding Algorithm Based On Digital Image

Reversible information hiding technology is different with the traditional information hiding technology in hiding information. The frontier one can recover the original carrier without distortion after correctly extracting the hiding information. It is extremely valuable in the situation which demands for high quality carrier signal, such as military, medical, court exhibit, electronic bill and etcReversible information hiding algorithm is designed based on prediction error expansion and histogram shifting. We discuss the influence of the order of prediction error expansion and histogram shifting. Histogram shifting causes error M1 after hiding information, prediction error expansion causes error M2 after hiding the same information. When M1≥M2, histogram shifting causes larger error, priority to hide secret information with prediction error expansion; when M1< M2, histogram shifting caused smaller error, priority to hide secret information with histogram shifting. Due to process pixel overflow, histogram shifting uses to record boundary value, prediction error expansion uses to choose images which are expanded without overflow.By the mode of histogram shifting to enhance the hiding capacity, the max peak point is different in different images. Therefore, the reversible information hiding algorithm is designed based on the prediction error sorting and multiple iterations. In order to improve the algorithm hiding capacity,we use multiple prediction error expansion to improve the algorithm hiding capacity. The higher capacity with the number of iterations increasing, the worse the image quality. In order to maintain image quality, we priority choose smaller prediction error image block to hide. To analyze and discuss two conditions:when hiding capacity equals to the maximum hiding capacity, the image quality can be guaranteed and greatly improve the hiding capacity; when hiding capacity is less than the maximum hiding capacity, we record block position to recover original image, and algorithm can maintain a certain image quality. Thus, you can select the corresponding treatment for different application scenarios.Finally, GUI is used to design a simulation system, which is used to verify the feasibility and effectiveness of the algorithm.