Efficient and parallelable image coding method oriented to sparse coefficients

A technology of image coding and sparse coefficients, which is applied in the field of image/video coding and decoding, can solve the problems of high computational complexity, difficulty in parallel processing, and high complexity, and achieve the effects of improving coding efficiency, easy parallel processing, and high coding efficiency

Inactive Publication Date: 2014-02-12
BEIHANG UNIV
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Problems solved by technology

The current organization method for sparse coefficients has certain limitations when choosing a data structure. For example, the combination of zero-tree structure and bit-plane coding for wavelet transform coefficients makes it difficult to achieve parallel processing. The organization of bit-plane coding does not make full use of the overall statistical properties of the transform coefficients, and requires the subsequent use of context-based adaptive arith...

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  • Efficient and parallelable image coding method oriented to sparse coefficients
  • Efficient and parallelable image coding method oriented to sparse coefficients
  • Efficient and parallelable image coding method oriented to sparse coefficients

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Embodiment

[0069] In order to describe in detail the coefficient organization method based on inter-frequency prediction, an example is given below.

[0070] Assume that the following are the transformation coefficients of two adjacent frequencies, which are the coefficients of the lower frequency and the coefficients of the higher frequency. From the energy distribution of the coefficients, it can be seen that their energy is mainly concentrated in the upper right corner area and the lower left corner area. The frequency coefficients are binned in 2×2, and the higher frequency coefficients are binned in 4×4.

[0071] 0 0 0 0 0 1 4 -1 0 -1 0 0 0 -1 -3 2 0 0 0 0 0 0 -1 0 0 -1 0 0 0 0 0 0 0 0 1 0 0 -1 0 0 0 1 -2 -1 0 0 0 0 -2 3 0 0 0 0 0 0 1 -1 0 0 -1 0 0 0

[0072] Table 1 Lower Frequency Coefficients

[0073] 0 0 0 0 0 0 0 0 0 0 0 0 -1 2 1 0

[0074] ...

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Abstract

The invention discloses an efficient and parallelable image coding method oriented to sparse coefficients. The method includes the following steps that (1) a coefficient organizational method based on inter-frequency prediction is utilized, the coefficients are converted with the block as the unit and in the sequence that block energy is progressively reduced, a dense region and a sparse region are divided, entropy coding is executed on the dense region, and an entropy coding method based on small probability coefficient representation in the step 2 is executed on the sparse region; (2) the conversion coefficients of the sparser region are coded by adopting the entropy coding method based on small probability coefficient representation, and then image coding is finished. The method is high in coding efficiency and supports parallel processing and asymptotic transmission, and code streams can be cut off.

Description

technical field [0001] The invention relates to a high-efficiency parallel image encoding method oriented to sparse coefficients, belonging to the technical field of image / video encoding and decoding, in particular to the encoding of transformation coefficients with sparse distribution characteristics. Background technique [0002] The objects of video coding and image coding are mainly natural signals. Natural signals have a strong correlation in the spatial domain. To improve the coding efficiency, the spatial domain signal must be processed first, and the correlation should be eliminated or weakened before coding. Transform coding is a process of removing correlation. The basic idea of ​​transform coding is to transform the image information described in the space domain into another orthogonal vector space (transform domain). After the alternating transformation, the correlation between the coefficients is basically eliminated, and the energy is mainly concentrated on ...

Claims

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Application Information

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IPC IPC(8): H04N19/61H04N19/63
Inventor 夏榆滨杨弢刘丰滔刘江胡阳
Owner BEIHANG UNIV
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