title: Authentication and recovery of medical diagnostic image using dual reversible digital watermarking.
abstract: This paper proposes a new region-based tampering detection and recovering method that utilizes both reversible digital watermarking and quad-tree decomposition for medical diagnostic image's authentication. Firstly, the quad-tree decomposition is used to divide the original image into blocks with high homogeneity, and then we computer pixels' linear interpolation as each block's recovery feature. Secondly, these recovery features as the first layer watermarking information is embedded by using simple invertible integer transformation. In order to enhance the proposed method's security, the logistic chaotic map is exploited to choose each block's reference pixel. The second layer watermark comprises by the quad-tree information and essential parameters for extraction are embedded by LSB replacement. In the authentication phase, the embedded watermark is extracted and the source image is recovered, and the similar linear interpolation technique is utilized to get each block's feature. Therefore, the tampering detection and localization can be achieved through comparing the extracted feature with the recomputed one, and the extracted feature can be used to recover those tampered regions with high similarity to their original state. Experimental results show that, compared with previous similar existing scheme, the proposed method not only achieves high embedding capacity and good visual quality of marked and restored image, but also has more accuracy for tampering detection.
authors.affiliation: School of Information Science and Engineering, Central South University, Changsha 410083, China.
authors.forename: Xiaohong
authors.initials: X
authors.lastname: Deng
authors.forename: Zhigang
authors.initials: Z
authors.lastname: Chen
authors.forename: Feng
authors.initials: F
authors.lastname: Zeng
authors.forename: Yaoping
authors.initials: Y
authors.lastname: Zhang
authors.forename: Yimin
authors.initials: Y
authors.lastname: Mao
mesh_terms: D003952:Diagnostic Imaging; D006801:Humans; D008279:Magnetic Resonance Imaging; D017711:Nonlinear Dynamics