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Smart City has become the direction of the development of city. Telemedicine is an important part of Smart City. Telemedicine always provides clinical health care according to the medical images of the patient. High resolution images are expected for remote diagnosis. Super-resolution technology can improve the resolution of medical images. Recently, sparse coding based super-resolution has attracted more attentions. Sparse coding based super-resolution tries to find the sparse representation of low-resolution (LR) image patches from low resolution dictionary, then reconstructs high-resolution (HR) image patches using sparse representation and HR dictionary. In this paper, we propose a sparse-based scheme for medical image super-resolution. First, we jointly divide the training patches into several clusters. Multiple dictionaries are learned from each cluster to collectively provide the least super-resolution error for the training patches. Second, random forest is trained based on the training patches and their cluster labels. Finally, for an input LR image patches, we use trained random forest to determine which cluster the patch belong to, then use the corresponding dictionary to reconstruct the patch. Thus, all the input LR patches are reconstructed with smallest error. All the reconstructed HR patches are synthesized into a completed HR image. The proposed scheme is applied to test a set of medical images. Experimental results show that both objective evaluation (PSNR) and subjective evaluation (visual effect) are improved when compare to other example-based methods.

The synchronisation between two floating memristor-based Colpitts oscillators is studied in this paper. Firstly, the mathematical and circuit models of Colpitts oscillator based on a floating memristor with a diode bridge structure are built. On this basis, numerical simulations on the features of both the independent memristor and the floating memristor are conducted and compared using MATLAB software. Secondly, circuit simulation is made on the synchronisation of two floating memristor-based systems by using MULTISIM software. Finally, the physical circuit on the synchronisation of the two coupling Colpitts systems based on the diode bridge memristors is implemented by using the linear error feedback scheme and improved by the capacitor coupling scheme and the adaptive nonlinear feedback control scheme, respectively. The experimental results by the oscilloscope and simulation results show that approximate synchronisation is achieved.

Video transmission over packet-switched networks usually suffers from packet losses. The use of the prediction loop in video coding will cause these errors to propagate to subsequent frames, and thus significantly impacts on the received video quality. With the increasing number of cameras to capture the scene, robustly delivering multi-view video over error-prone channels becomes a rather challenging task. A rate-distortion optimization algorithm is proposed to improve error resilience for multi-view video transmission. A recursive model to estimate the end-to-end distortion is developed for multiview video coding, in which the distortion model explicitly takes into consideration the inherent error resilience property of the hierarchical bi-prediction structure. Based on the proposed distortion model, end-to-end rate-distortion optimization criterion is employed to perform coding mode switching. Extensive experimental results demonstrate significant performance gains can be achieved for multi-view video communication against transmission errors.

In the joint mode of MVC (Multiview Video Coding), to fully exploit both temporal and inter-view correlation, motion estimation (ME) and disparity estimation (DE) have been employed to achieve the highest coding efficiency. However, it causes enormous computational complexity. An adaptive ME and DE algorithm is proposed to reduce the complexity in this paper. Fist, we calculate the difference between the coding macroblock (MB) and the corresponding MB in the reference frame to determine the region homogeneity. Then, based on the region homogeneity, some INTER modes will be skipped in coding mode selection. Finally, an optimization method of obtaining the optimal motion information from the neighboring view is proposed to speed up rate distortion optimization (RDO) process for Motion Skip (MS) mode. In addition, the search range (SR) for ME and DE can be limited to an estimable range and the disparity search is selectively enabled adaptively. Experimental results demonstrate that the proposed algorithm can save about 78% computational complexity on average, with negligible loss of encoding efficiency.