In the non-rigid point set registration algorithm, whether the correct correspondence can be found plays an important role. Generally the corresponding points in two point sets have similar neighborhood structures besides the close distance. Therefore, a non-rigid point set registration algorithm based on global and local similarity measurement was proposed. Firstly, the Coherent Point Drift (CPD) algorithm was used as the registration framework, and the Gaussian mixture model was used to model the point sets. Secondly, the global and local mixture distance was improved to form the global and local similarity measurement criterion. Finally, the correspondence and the transformation formula were solved by the Expectation Maximization (EM) algorithm. In the initial stage of the iteration, the proportion of local similarity was larger so that the correct correspondence was able to be found rapidly; with the progress of the iteration, the proportion of global similarity was increased to ensure the smaller registration error. Experimental results show that compared with the Thin Plate Spline Robust Point Matching (TPS-RPM) algorithm, the Gaussian Mixture Models point set REGistration (GMMREG) algorithm, the Robust Point Matching algorithm based on L ₂E estimation (RPM-L2E), the Global and Local Mixture Distance and Thin Plate Spline based point set registration algorithm (GLMDTPS) and the CPD algorithm, the proposed algorithm has the Root Mean Squared Error (RMSE) decreased by 39.93%, 42.45%, 32.51%, 22.36% and 11.76% respectively, indicating the proposed algorithm has better registration performance.

Aiming at the problem of object structure discontinuity and incompleteness occurred in image completion, an image completion algorithm based on depth information was proposed. Firstly, the plane parameter Markov random field model was established to speculate depth information of the pixels in the image where the scene situate, then the coplanar region in the image determined, and the target matching blocks were located. Secondly, according to the principle of perspective projection, the transformation matrix was derived, which guided the geometric transformation of the matching blocks. Finally, the target cost function which includes the depth term was designed. Experimental results show the proposed algorithm has superiority in both subjective details and Peak Signal-to-Noise Ratio (PNSR) statistics.

The traditional patch-based image completion algorithms circularly search the most similar patches in the whole image, and are easily affected by confidence factor in the process of structure propagation. As a result, these algorithms have poor efficiency and need a lot of time for the big computation. To overcome these shortages, a fast image completion algorithm based on randomized correspondence was proposed. It adopted a randomized correspondence algorithm to search the sample regions, which have similar structure and texture with the target region, so as to reduce the search space. Meanwhile, the method of computing filling priorities based on confidence factor and edge information was optimized to enhance the correctness of structure propagation. In addition, the method of calculating the most similar patches was improved. The experimental results show that, compared with the traditional algorithms, the proposed approach can obtain 5-10 times speed-up in repair rate, and performs better in image completion.

In order to solve the problem that channel resource cannot be fully utilized by single-path routing protocol in multi-channel wireless mesh networks, a Parallel Multi-path Routing Protocol (PMRP) based on congestion control was proposed. This protocol spread a data flow over multiple paths and only re-found new route after all routes have broken. It prevented the congested node to transmit new data flow by utilizing congestion control mechanism. The simulation results demonstrate that, compared with Ad hoc On-demand Distance Vector Routing (AODV) routing protocol, PMRP can reduce the average end to end delay, and improve the data packet delivery ratio and the network throughput effectively.