Research Of Compression Algorithm For Video Based On Multi-dimensional Walsh Vector Orthogonal Matrix

With the fast development of science and technology, image and video have moved from natural world into nowadays computer. The key technique that makes this change happen is due to the color image(video) compression method. The reason is that if a certain color image(video) is uncompressed, it may take up quite large memory space up to several gigabits, which would be difficult for people to transmit and storage huge volume of color images in computer network. On the contrary, the color image(video) compressed takes up much lesser space, which makes it possible to transmit and store large amount of images under practical circumstances.The reason that the color image(video) can be compressed lies in the fact that it contains different kinds of redundancies from the viewpoint of information theory. Of course, we are unable to find the inner principals existing in image(video) data though humans'eyes. However, we can find these redundancies with the help of modern statistics theory. For example, pertinence exists among pixels and also among components of each one pixel, both of which are classical representatives of color image redundancies. Generally speaking, the redundancy of the color image(video) comprises of statistic redundancy, structure redundancy, knowledge redundancy, vision redundancy and color space redundancy, etc.Traditionally, the simple mathematical model of two-dimensional matrix can not meet the requirements of multi-dimensional digital images processing. So many scholars both at home and abroad are committed to find a new mathematical model. They do their research on the geometry, tensor and other mathematical tools trying to show the image sequence using more effective multi-dimensional model, but all of them are not suitable. At present, a large number of methods which can improve compression performance of multi-signal are only based on the accumulation of small improvements. On the basis of the introduction of 4-D n order matrix, we defined the orthogonal transform method of 4-D n order matrix space, and the orthogonal square matrix of the model is found. Finally, the multi-data are processed universally in a unity cubic model to get a better compression effect..In this paper, we first introduced the video coding theory,such as Predictive Coding,Transform Coding and entropy coding. We also introduce international standards,for example:JPEG, H.26X, MPEG, AVS.Due to the traditional encoding theory doesn't consider the redundancy of the YUV or RGB frames. Our laboratory has proposed a new expression idea named multi-dimensional matrix theory, which is capable of expressing the three consecutive frames of a color image and video into a whole mathematical model to reduce its color redundancy. With the theory of 4-D nth order matrix, the model has been used in the color image and video compression. Unlike the traditional matrix theory, our 3-D matrix theory focuses on the reduction of color space redundancy such that it can further improve the image compression ratio.In this paper, the theory of multi- dimensional vector matrix redefines the concept of multi- dimensional matrix, which makes the multiplication of the matrixes is more flexible and universal. The paper also extends the application of the color image compression to the color video compression, and proposes the 4-D Walsh vector orthogonal transform matrix on the basis of 4-D nth Hadamard orthogonal transform matrix, which has more flexibility.Finally, this paper lists out the performance of the 4-D nth order matrix orthogonal transform by using Visual C ++ 6.0 under Windows environment. The experimental results of our algorithm have shown its better concentration for energy, which definitely proves the effectiveness of our algorithm.However, the 4-D vector Walsh orthogonal transform matrix which is based on the theory of multi- dimensional vector matrix is still a new image compression algorithm and surely needs further improving. For instance, the decoded video has blocking effect, so we could use the multi-dimensional loop-filter to eliminate the blocking effect. In addition, we should find the finest scanning and encoding method to improve the compression ratio.