In this paper, we propose a wavelet-based fast motion estimation algorithm for video sequence encoding with a low bit-rate. By using one of the properties of the wavelet transform, multi-resolution analysis (MRA), and the spatial interpolation of an image, we can simultaneously reduce the prediction error and the computational complexity inherent in video sequence encoding. In addition, by defining a significant block (SB) based on the differential information of the wavelet coefficients between successive frames, the proposed algorithm enables us to make up for the increase in the number of motion vectors when the MRME algorithm is used. As a result, we are not only able to improve the peak signal-to-noise ratio (PSNR), but also reduce the computational complexity by up to 67%.
In this paper, effective algorithms for stereoscopic video coding and multi-view coding which are used in 3DAV coding are proposed. In the proposed algorithm, we refer to disparity vectors of adjacent blocks as parameters of the predictor for the disparity vector of current block. Disparity vectors of adjacent blocks extend the usability of the homogeneity. In an object, adjacent block disparities are very similar. These similar vectors result to reduce computational power. Block matching algorithm sometimes gives reconstructed image distortion. In multi-view system, this happens usually in occlusion region or region around edges. Partially matched block needs to divide blocks in quad blocks or smaller blocks to reduce this distortion. Coarse to fine hierarchical algorithm is able to get rid of noise from incorrect matching of a pixel based matching algorithm. And it also reduces computational complexity in finding matched block or pixel. There may be overall luminance difference between multi-view images caused by viewer positions. This problem can be solved by block recursive matching algorithm(BRMA). Experimental results show that this algorithm gives under 80% of calculation load and better image quality at over 0.6dB of PSNR in tested images comparing with symmetric BMA.