Concerning the problem that existing Intra Bock Copy (IBC) algorithm is not well suitable to the screen content with a variety of different sizes and shapes of patterns, an Intra Mini-Block Copy (IMBC) algorithm was proposed to further improve coding efficiency of the screen content. Firstly, the Coding Unit (CU) was divided into a set of L mini-blocks. Secondly, each mini-block was taken as the smallest matching and replication unit, the reference mini-block which matched the mini-block best was found in the reference set R by a mini-block matching optimal selection strategy. And the location of the reference mini-block and its location in the current CU were specified by L Displacement Vectors (DVs). Finally, a prediction algorithm was firstly applied to the L DVs for eliminating the correlation between DVs before entropy encoding. Compared with the IBC algorithm, for the High Efficiency Video Coding (HEVC), Screen Content Coding (SCC) test sequences, IMBC achieved the BD-rate reduction up to 3.4%, 2.9%, 2.6% for All Intra (AI), Random Access (RA) and Low-delay B (LB) configurations in lossy coding respectively, and the Bit-rate saving up to 9.5%, 5.2%, 5.1% for AI, RA, LB configurations in lossless coding respectively. The experimental results show that IMBC algorithm can effectively improve the coding efficiency of screen image at very low additional encoding and decoding complexity.

The high complexity and long computing time of Scale-Invariant Feature Transform(SIFT) algorithm cannot meet the real-time requirements of stereo matching. And the mismatching rate is high when an image has many similar regions. To solve the problems, an improved stereo matching algorithm was proposed. The proposed algorithm was improved in two aspects. Firstly, because the circular has natural rotation invariance, the feature point was acted as the center and the rectangle region of the original algorithm was replaced by two approximate-size concentric circle regions in the improved algorithm. Meanwhile, the gradient accumulated values of 12 directions were calculated within the areas of the inner circle and the outer circle ring respectively, and the dimension of the local feature descriptor was reduced from 128 to 24. Then, a 12-dimensional global vector was added, so that the generated feature descriptor contained the SIFT vector based on local information and the global vector based on global information, which improved the resolving power of the algorithm when the images had similar areas. The simulation results show that, compared with the original algorithm, the real-time performance of the proposed algorithm was improved by 59.5% and the mismatching rate was decreased by 9 percentage points when the image had many similar regions. The proposed algorithm is suitable for in the case of high real-time image processing.

To solve the problem of that although Intra String Copy (ISC) improved the effect of the screen content coding, but it transformed the 2D image to 1D by Coding Unit (CU), making adjacent regions in an image segmented and spatial correlation not to be used, a new algorithm called 2D Intra String Copy (2D ISC) was proposed. Almost without additional memory in encoder and decoder, the algorithm realized arbitrary 2D shape searching and matching without boundary restriction of CU for pixels in current CU, by using dictionary coding tool in High Efficiency Video Coding (HEVC) reconstruction cache. Also adopted technologies of color quantization preprocessing and horizontal vertical search order self-adaption to enhance coding effect. Experiments on common test for typical screen content test sequences show that compared with HEVC, 2D ISC can achieve bit-rate saving of 46.5%, 34.8%, 25.4% for All Intra(AI), Random Access(RA) and Low-delay B(LB) configurations respectively in lossless coding mode, and 34.0%, 37.2%, 23.9% for AI, RA and LB configurations respectively in lossy coding mode. Even compared with ISC, 2D ISC can also achieve bit-rate saving up to 18.3%, 13.9%, 11.0% for AI, RA and LB configurations in lossless coding mode, and 19.8%, 20.5%, 10.4% for AI, RA and LB configurations in lossy coding mode. The experimental results indicate that the proposed algorithm is feasible and efficient.

The high speed of the information propagation exacerbates the diffusion of rumors or other network pollutions in the microblogging. As the size of microbloggers and information of sub-networks in microblogging is enormous, the study of the propagation mechanism of microblogging pollution and pollution detection becomes very significant. According to the rumor spreading model for the microblogging established on the basis of influence of users, in this paper, ant colony algorithm was used to search for the rumor spreading route. Based on the data obtained from Twitter and Sina microblogging, the feasibility of the model was verified by comparison and analysis. The results show that: with the search of the affected individual, this model narrows down the pollution detection range, and improves the efficiency and accuracy of pollution management in microblogging.