Research Of Motion Estimation And Compensation Algorithms In Video Compression Based On Redundant Discrete Wavelet Transform

The study of the video compression coding algorithms is one of the most active areas in the information technology now. Motion estimation and compensation play a virtual role in video compression coding to reduce temporal redundancies. Block matching algorithm (BMA) in the spatial domain is widely employed in modern video compression systems.Now one hot spot in the research of video compression coding is the motion estimation algorithm based on the Discrete Wavelet Transform (DWT) became of its good time-frequency localization characteristics and match the human visual system. However, DWT isn't shift invariant so that the motion estimation deployed in the wavelet domain can't get good performance.Because the Redundant Discrete Wavelet Transform (RDWT) is shift invariant, the motion estimation algorithms in the redundant wavelet domain have good performance,but very high computational complexity. BMA is based on the translational model,so it has some limits and shortages.However, triangulation-mesh-based motion estimation is based on the affine transform,it amends the shortages of BMA and has a good motion estimation and compensation effect for the video sequence whose motion is non-translational.The breakthrough point of this dissertation is how to ulteriorly improve the precision and efficiency of motion estimation and compensation and the subjective quality of reconstructed image and reduce computational complexity. This dissertation mainly researches the block matching motion estimation and compensation algorithms based on the redundant discrete wavelet domain and the DT mesh motion estimation algorithms based on the redundant discrete wavelet domain for the video sequence whose motion is non-translational.The main research of this dissertation is listed as follows:This dissertation introduces the method for starting point prediction and search algorithm in spatial domain into the motion estimation algorithms in the redundant wavelet domain, and a fast adaptive block matching motion estimation and compensation algorithms based on the redundant wavelet domain is proposed. Fistly, this algorithm proposes a method of calculating adaptive threshold for dividing motion degree of image blocks and stopping search automatically. And potential motion blocks can be extracted by using adaptive threshold. Then, an adaptive method for starting point prediction is proposed in the redundant wavelet domain to realize the precise prediction of starting point of potential motion blocks. Finally, based upon the motion characteristics of the subjects in the video image and the improvement of search algorithm in spatial domain, an adaptive search algorithm in the redundant wavelet domain is proposed to realize the fast motion estimation of potential motion blocks, which can adjust the direction and radius of search and threshold of stopping search adaptively. The result of experiment indicates that this algorithm can maintain a higher peak signal to noise ratio and reduce the time of motion estimation effectively and improve the efficiency of motion estimation. And the subjective quality of reconstructed image is good. This approach has a remarkable performance compared with the existing block matching motion estimation algorithm in redundant wavelet domain in terms of the precision and efficiency. Especially, this algorithm has very strong adaptive capacity for the video sequences which has different motion characteristics.Because BMA dosen't have a good motion estimation and compensation for the video sequence whose motion is non-translational. Based upon the traditional DT mesh motion estimation algorithms, an DT mesh motion estimation algorithms in redundant wavelet domain based on improved SIFT for extracting feature is proposed. Fistly, this algorithm proposes a new template for extracting feature point and introduces SIFT algorithm in spatial domain into extraction of feature point in the redundant wavelet domain. Then,an improved SIFT algorithm of rotation-resistant and low dimension feature descriptor is proposed and a new feature point similarity measure and matching criterion are proposed. Then, feature point extracting and matching are made in new template using improved SIFT algorithm and feature matching criterion. And DT mesh is generated with matched feature point regarded as mesh node. Fistly, potential motion area (PMA) was extracted in redundant wavelet domain and DT mesh motion estimation and compensation was done in PMA by motion vector of mesh node and the affine transform. The result of experiment indicates that this algorithm can extract feature points of the video sequences fast and effectively and make feature matching accurately, and get accurate motion vector and improve the precision and efficiency of motion estimation. And the subjective quality of reconstructed image is good. This approach has a superior performance compared with the raditional DT mesh motion estimation algorithm in redundant wavelet domain in terms of the predict precision and efficiency, especially for the video sequences whose motion is non-translational.