By Wen Gao, Siwei Ma
This booklet provides an outline of the state-of-the-art in video coding know-how. in particular, it introduces the instruments of the AVS2 average, describing how AVS2 may help to accomplish an important development in coding potency for destiny video networks and functions by means of incorporating smarter coding instruments equivalent to scene video coding. gains: introduces the fundamental techniques in video coding, and offers a quick background of video coding know-how and criteria; stories the coding framework, major coding instruments, and syntax constitution of AVS2; describes the foremost applied sciences utilized in the AVS2 commonplace, together with prediction coding, remodel coding, entropy coding, and loop-filters; examines effective instruments for scene video coding and surveillance video, and the main points of a promising clever video coding procedure; discusses optimization applied sciences in video coding platforms; offers a evaluate of photo, video, and 3D content material caliber review algorithms; surveys the new study subject matters in video compression.
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Additional info for Advanced Video Coding Systems
In 1965, Enomoto and Shibata (1965) first proposed a practical video compression method with one dimensional Hadamard transform. In 1968, Andrews and Pratt (1968) extended the Enomoto’s method to two dimensional transform with block-based Fourier transform. However, the Fourier transform has a relative high computational complexity, which is difficult to apply in practical video coding system. In 1973, Chen (1973) proposed Slant transform and the corresponding fast computational algorithm, which has higher energy compaction property than Fourier transform.
Spatial motion vector prediction is used for spatial derivation of Skip/Direct mode in F frames and B frames. Temporal motion vector prediction is used for temporal derivation of Skip/Direct mode in B frames. Spatial-temporal combined motion vector prediction is used for temporal derivation of Skip/Direct mode in F frames. For other cases, median prediction is used. In AVS2, the motion vector is in quarter-pixel precision for the luminance component, and the subpixel is interpolated with an 8-tap DCT interpolation filter (DCT-IF) (Lv et al.
8 Vertical and horizontal locations of 4:2:2 (left) and 4:4:4 (right) luma and chroma samples in a picture Besides the sampling rate, the sampling precision of each component of YUV is also an important parameter, called bit depth or color depth, which decides the number of colors represented by YUV. , 4-bit color or 8-bit color (use 4 or 8 bits to represent all the colors directly, not for each color component). 2 Video Formats 27 would be inescapable. In the industry, HDMI (High-Definition Multimedia Interface) has defined 30, 36, and up to 48-bit color for more vivid color display.
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