In order to filter out Gaussian noise and impulse noise at the same time, and get high resolution image in super-resolution reconstruction, a method with L₁ and L₂ mixed norm and Bilateral Total Variation (BTV) regularization was proposed for sequence images super-resolution. Firstly, multi-resolution optical flow model was used to register low-resolution sequence images and the registration precision was up to sub-pixel level, then the complementary information was used to raise image resolution. Secondly, taking advantage of L₁ and L₂ mixed norm, BTV regularization algorithm was used to solve the ill-posed problem. Lastly, the proposed algorithm was used to sequence images super-resolution. Experimental results show that the method can decrease the mean square error and increase Peak Signal-to-Noise Ratio (PSNR) by 1.2 dB to 5.2 dB. The algorithm can smooth Gaussian and impulse noise, protect image edge information and improve image identifiability, which provides good technique basis for license plate recognition, face recognition, video surveillance, etc.

To solve the problems of three-dimensional clipping and Multi-Planar Reformation (MPR) that only the geometrical information of the tissues or organs can be obtained and the structure of a curving organ cannot be displayed in a single image, a Curved Planar Reformation (CPR) algorithm based on MPR to extract the outline was proposed to reform the coronary artery. Firstly, the discrete points expressing the outline of the coronary artery were extracted by using MPR. Afterwards, the Cardinal interpolation was used to get smooth outline fitting curve. Secondly, the outline was projected along the interested direction to get the scanning curved planar. Finally, the scanning curved planar corresponding to the volume data of the cardiac was displayed, so the CPR image of artery was got. The experimental results show that, compared with three-dimensional clipping method and three-dimensional data field method, the increment for the extracting speed of the coronary artery outline is about 4 to 6 frames per second, and the rendering time is shorter. On the aspect of rendering quality, compared with three-dimensional segmentation method, the image of coronary artery curved plane is clear and complete, which is helpful for doctors to analyze the lesion clearly and satisfies the demands of actual clinical diagnosis.