Motion estimation is a core process for video coding schemes, which enables the transmission and storage of video signals with a low bit rate. In order to decrease calculation times and enhance matching efficiency of block matching search, a fast block matching motion estimation algorithm based on edge partial distortion search was proposed. Based on the block matching criterion, the algorithm forecasts the motion vector by sorting the similarity between the current image block and its neighborhood image block, and then chooses the motion vector of neighborhood image block with the highest similarity as its own motion vector. At the same time, edge partial distortion strategy was introduced, and the computing of neighborhood image block with the bigger deviation was prematurely terminated. The simulation result shows that the algorithm reduces the calculation amounts and promotes the matching precision in comparison with other fast standard block matching methods.

Image superresolution(SR) reconstruction technique is how to produce a clearly high resolution(HR) image from the information of one or several low resolution(LR) images, and it has been received increasing attention from the image processing community. In the paper, the fundamental principles and mathematical models of SR technology based on reconstruction were described firstly, and the history and stateofart of image SR reconstruction were stated briefly according to the classification between the frequency domain method and the space domain method. Secondly, advantages and defects of different methods were analyzed and summarized systematically. Finally, the further research directions for image SR technique of reconstructing based the approach were proposed.

Engineering design revolved a lot of design data. Partial design data were described in the form of curve chart. Spiral angle coefficient curve was a typical engineering curve and had the characteristics of engineering curves. In the paper, spiral angle coefficient curve was as an example in which scanning image preprocessing, image revision, image cropping, binarization processing, mesh removing, characteristics point extracting of spiral angle coefficient curve were put forward. Furthermore, the least square method was used to fit characteristic points and accomplish digitizing of engineering curves.