This paper extends the theory of multi-dimensional vector orthogonal transformation matrix and presents a new 4D order-4 DCT integer transform operator based on the theory of multi-dimensional vector matrix discrete cosine transform (MD-VMDCT). Meanwhile, the orthogonality of the operator and energy concentration is verified in the paper. Also the comparison between the integer and the float 4D-VMDCT is carried out. At last, the video sequence is compressed using our approach. The experimental results show that the algorithm is correct and effective. It is better than H.264/AVC under the same conditions and it is slightly lower in performance compared with float 4D-VMDCT.
This paper proposes a technique for generating the quantisation cube and an improved zigzag scanning method suitable to multidimensional vector matrix DCT integer transform (MD-VMICT) codec after studying the statistical properties of the DC and AC coefficients. An e-exponential function is used to quantisation and it is verified to twoexponential function in order to easily carrying out by shift operator. After determining the proper parameter by experiments, the proposed quantisation and scan order are tested on various standard test video sequences. The experiments show the wide adaptability. Also the comparisons are carried out with the literature and MPEG-4, whose experiment results show superiority than the literature and MPEG-4. The comparisons between MD-VMICT and H.264/AVC show potential advantages at low bit rate with high activities sequences.
Multiview video (MVV) is multiple video sequences that integrated different viewpoints data of the same three-dimensional (3D) scene. Each viewpoint data are taken from the ordinary video camera. Thus, the data are very large for the MVV. So compression is necessary in order to store and transmit effectively. Based on the theory of multi-dimensional vector matrix (MDVM), we propose a six-dimensional (6D) vector orthogonal transform nuclear matrix, and prove its orthogonality and energy concentration. We apply the theory to multiview video coding (MVC). This transformation is based on discrete cosine transform (DCT), which has the optimal performance for video data. We represent MVV data with a multi-dimensional (MD) mathematical model. The chosen MVV is earlier eight frames in YUV format from two viewpoints. We divide the Y, U and V components into cubes respectively, and combine the two views data into one cube, on which the transformation is conducted. Good results are obtained in terms of energy concentration. This paper provides a new method for handling MVV, and prepare for the next quantisation and coding.
Nowadays, the 3D discrete cosine transform (DCT) is applied widely in video coding. But the transform matrix of DCT is expressed with floating-point numbers, so the computational complexity is high, and more system resources are occupied. In addition, the 3D DCT is accomplished by operating 1D DCT to the rows, columns and pages of 3D data successively, which cannot embody the overall space performance of 3D transform well. To overcome these drawbacks, 3D integer submatrix discrete cosine transform (SDCT) method was proposed in the paper. First, several matrix operation methods were defined. Then, the basic principle and calculation method of 3D integer SDCT was deduced in detail. The main idea was to take the 3D data as a whole, and adopt the integer transform matrix instead of the floating-point transform matrix. Finally, the performances of 3D integer DCT operation were analysed, and the experimental results show that the transform effects based on 3D integer SDCT and 3D DCT are very similar.
Nowadays, a well-established video coding method is based on the block-matching algorithm that is in the core of all MPEG and H.26x standards. However, this method involves motion estimation and compensation; thus the computational complexity is high. However, the video coding based on three-dimensional discrete cosine transform (3D DCT) is a potential method, and the scanning order and quantisation of 3D DCT coefficients play a crucial role in coding effect. So, the statistical performances of 3D DCT are studied in this paper, and then adaptive scanning order and quantisation of 3D coefficients are proposed. The theoretical analysis and experiment results show significant improvement in performance over previously reported methods.
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