Wavelet transform is a popular tool for image and video coding. It has several advantages in multiresolution analysis and subband decomposition of images. Motion estimation and motion compensation methods are widely used to reduce temporal redundancy in video sequences. Although there have been several attempts to compensate for the motion in the wavelet domain, their performances are limited due to the shift-variant problem. In this paper, we propose a new motion compensation method in the wavelet domain to overcome the shift-variant problem. Experimental results show that the proposed method outperforms the previous motion compensation methods in the wavelet domain as well as the full search algorithm in the spatial domain.
For video compression, motion estimation is popularly employed to exploit temporal correlation existing in video sequences. If we employ the full search block matching algorithm for estimating motion vectors, it requires very heavy computational complexity. Although several fast block matching algorithms have been proposed to solve this problem, they sacrifice their reconstructed image quality. In this paper, we derive optimal search patterns for fast block matching motion estimation. By analyzing the block matching algorithm as a function of the block size and the shape, we find optimal search patterns for initial motion estimation. The proposed idea can provide an analytical ground for the current MPEG-2 proposals. In addition, we propose a new fast motion estimation algorithm using adaptive search patterns, considering matching criteria and statistical properties of object displacement. In order to select an appropriate search pattern, we exploit the relationship between the motion vector and the frame difference of each block. By changing the search pattern adaptively, we can improve the motion prediction accuracy, while reducing the required computational complexity compared to other fast block matching algorithms.
In this paper, we examine new motion compensation methods based on the affine or bilinear transformation and derive fast algorithms for affine and bilinear transformation using vector relationship. We also develop a more effective motion estimation method than the conventional image warping method in terms of computational complexity, reconstructed image quality, and the number of coding bits. The performance of the proposed motion compensation method, which combines the affine or the bilinear transformation with the proposed adaptive partial matching, is evaluated experimentally. We simulate our proposed motion compensation method in a DCT- based coder by encoding CIF (Common Intermediate Format) images at bitrates of below 64 kb/s. The proposed adaptive partial matching method can reduce the computational complexity below about 50% of the hexagonal matching method, while maintaining the image quality comparable to the hexagonal method.