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Hadamard transform-based fast intra-prediction mode selection and PU partition method

A mode selection and intra-frame prediction technology, applied in digital video signal modification, electrical components, image communication, etc., can solve problems such as high computational complexity

Active Publication Date: 2016-10-12
XIDIAN UNIV
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Problems solved by technology

[0015] Although a fast mode selection algorithm is adopted in HM, which reduces the amount of calculation, the computational complexity is still very high.

Method used

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  • Hadamard transform-based fast intra-prediction mode selection and PU partition method
  • Hadamard transform-based fast intra-prediction mode selection and PU partition method
  • Hadamard transform-based fast intra-prediction mode selection and PU partition method

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Embodiment Construction

[0050] Such as figure 2 , 3 , 4, a Hadamard transform-based intra prediction fast mode selection and PU division method, the algorithm is nested in the fast mode selection algorithm of HM16.0, the method includes the following steps:

[0051] S1. Use the Haddmard transform to obtain the complexity of the current PU block, which is recorded as NI; at the same time, record the complexity of the current 64*64 PU block as N2;

[0052] S2. Determine whether the current PU is 8*8 blocks? If yes, execute S3, otherwise execute S4;

[0053] S3. Compare N1 with the threshold ζ, if N1ζ, continue to traverse 4 *4 PU blocks, after that execute S4;

[0054] where ξ=N2 / 64

[0055] S4. Compare N1 with the complexity threshold ε of the current PU depth; if N1<ε, execute S5, otherwise execute S6, where ε=12500, 2500, 800, and the PU size is 16*16, 8*8, 4 respectively *4;

[0056] S5, instead of traversing 35 candidate models, but traversing the new candidate model list modelist, selecti...

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Abstract

The present invention discloses a Hadamard transform-based fast intra-prediction mode selection and PU partition method, including: 1. according to complex conditions of image texture, reducing the amount of computation and traversing PU; 2. performing Hadamard transform on a current PU block, to obtain the complexity of the current PU block; 3. judging whether the texture of the current PU block is complicated according to the complexity of the current PU block as the metric of the image texture; 4. if the texture of the current PU block is complicated, for the PU, traversing 4*4 partition modes; and for mode selection, traversing 35 candidate modes; and 5. if the current PU block is gentle and smooth, for the PU, partitioning into large pieces more probably without traversing 4*4 partition modes; and for mode selection, traversing few candidate modes only. The method disclosed by the present invention reduces a lot of amount of computation, and greatly reduces the coding time with performance reduction within the acceptable range, thereby improving the timeliness of HM.

Description

technical field [0001] The present invention relates to the field of the new-generation video coding standard HEVC, in particular to a method for fast mode selection and PU division of intra-frame prediction based on Hadamard transform. The present invention is implemented based on software, and is not limited to specific video sequences and resolutions, can greatly reduce the encoding time of intra-frame prediction, and improve the real-time performance of HEVC encoding without causing too much performance degradation. technical background [0002] HEVC (High Efficiency Video Coding) is a new generation of video coding standard after H.264. Its core purpose is to double the video compression efficiency on the basis of H.264 to meet people's increasingly strong demand for high-quality video. demand. However, the improvement of encoding performance also brings high computational complexity, which directly affects the encoding rate. Therefore, reducing the coding complexity ...

Claims

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Application Information

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IPC IPC(8): H04N19/61H04N19/109H04N19/122H04N19/147H04N19/176
CPCH04N19/109H04N19/122H04N19/147H04N19/176H04N19/61
Inventor 宋锐李璐李云松王养利赵园伟
Owner XIDIAN UNIV
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