It is of great importance in telemedicine to protect authenticity and integrity of medical images. They are mainly addressed by two technologies, which are region of interest (ROI) lossless watermarking and reversible watermarking. However, the former causes biases on diagnosis by distorting region of none interest (RONI) and introduces security risks by segmenting image spatially for watermark embedding. The latter fails to provide reliable recovery function for the tampered areas when protecting image integrity. To address these issues, a novel robust reversible watermarking scheme is proposed in this paper. In our scheme, a reversible watermarking method is designed based on recursive dither modulation (RDM) to avoid biases on diagnosis. In addition, RDM is combined with Slantlet transform and singular value decomposition to provide a reliable solution for protecting image authenticity. Moreover, ROI and RONI are divided for watermark generation to design an effective recovery function under limited embedding capacity. Finally, watermarks are embedded into whole medical images to avoid the risks caused by segmenting image spatially. Experimental results demonstrate that our proposed lossless scheme not only has remarkable imperceptibility and sufficient robustness but also provides reliable authentication, tamper detection, localization, and recovery functions, which outperforms existing schemes for protecting medical images.

This paper presents an observer-based robust control (ORC) scheme, combining perturbation observers with fractional-order sliding-mode regulators, for the current control of rotor-side converter (RSC) of a doubly-fed induction generator (DFIG). Perturbation states are defined to describe the interactions between d-axis and q-axis rotor current loops. The decoupled current control of RSC is realized via fractional-order sliding-mode output feedback control and perturbation compensation based on the estimation states obtained by perturbation observers. The proposed ORC scheme does not require any parameters of DFIG and it is robust to system uncertainties and external disturbances. Experimental tests are undertaken on a hardware-in-the-loop DFIG system to verify the control performance of ORC scheme.

The Discrete cosine transform (DCT) and inverse Discrete cosine transform (IDCT) have been widely used in image and video compression standards, and more and more researchers focus on the method that taking use of the coordinate rotation digital computer (CORDIC) to execute the DCT and IDCT, the reason is that CORDIC can realize the complex transcendental functions only by using shifters and adders, and is easily suitable implemented in a parallel way. However, the conventional CORDIC has some drawbacks, such as low precision, long iteration number, scale factor and so on. In our previous paper, we have implemented an unified DCT/IDCT based on adaptive recoding CORDIC (ARC) to improve the performance. In this paper, compared with our previous work, we propose an enhanced unified architecture for DCT and IDCT based on the cooperation between the enhanced adaptive recoding coordinate rotation digital computer (EARC) and the conventional CORDIC, in which the radix-2 scale factor approximation proposed in our previous paper is also optimized significantly to achieve better performance in power consumption and PSNR. To conduct a fair competition, the proposed architecture is also validated on a Virtex 5 FPGA platform to evaluate the performance. Under DCT only mode, compared with the Huang and Lee architectures, the proposed architecture at least uses 3.3% less area, dissipates 9% less power at the nearly 2% cost of the critical path delay. Under DCT/IDCT mode, the proposed architecture also saves over 2% hardware resources, reduces more than 5.9% power dissipation when compared to the latest unified DCT/IDCT architectures. Meanwhile, the proposed architecture exceeds the state-of-the-art unified architectures over 0.98 dB in PSNR. Compared with 2S-8P-DCT and 3S-8P-DCT, the proposed unified DCT/IDCT architecture also achieves the best performance in accuracy, processing time and throughput.