Fast intra mode decision and block matching for HEVC screen content compression

Zhang, Hao; Zhou, Qiao; Shi, Ningning; Yang, Feng; Feng, Xin; Ma, Zhan

doi:10.1109/icassp.2016.7471902

Cited by 25 publications

(101 citation statements)

References 10 publications

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“…These are categorised into mainly three types: fast coding depth decision [2][3][4][5][6][7][8], fast prediction mode decision [9][10][11][12][13][14][15][16][17][18][19] and hybrid fast scheme [20][21][22][23][24][25][26]. Some typical algorithms in each category are described as follows:…”

Section: Related Workmentioning

confidence: 99%

“…Shen et al [3] proposed a fast CU size decision scheme, where large CU sizes can be bypassed depending on the texture homogeneity. In [4], a fast CU depth prediction method was proposed for HEVC screen content compression. The temporal correlation of co-located CUs was exploited to predict the most likely mode, and an adaptive search step approach was used to further accelerate the block matching process of intra block copy (IBC) mode.…”

Section: Related Workmentioning

confidence: 99%

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A fast HEVC intra-coding algorithm based on texture homogeneity and spatio-temporal correlation

Xuesong

2018

EURASIP J. Adv. Signal Process.

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The high efficiency video coding (HEVC) standard supports a flexible coding tree unit (CTU) partitioning structure, and thus coding efficiency is improved significantly. However, the use of this technique inevitably results in greatly increased encoding complexity. In order to reduce the complexity of intra-coding, we propose a hybrid scheme consisting of fast coding unit (CU) size decision and fast prediction unit (PU) mode decision processes. An adaptive method is utilised to measure the homogeneity of video content thus avoiding unnecessary rate distortion (RD) evaluations. The depth range to be tested is narrowed based on the partitioning parameters of the spatially adjacent CUs and the temporally co-located CU. Furthermore, the mode correlation between neighbouring frames and between adjacent coding levels in the same quad-tree structure is taken into account to predict the most probable directional mode. The number of candidate PU modes is further decreased according to the Hadamard cost. Experimental results illustrate that our scheme achieves a significant reduction in computational complexity of HEVC intra-coding. Compared with the HM encoder, the encoding time is reduced by up to 71% with negligible degradation in coding efficiency.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

A fast HEVC intra-coding algorithm based on texture homogeneity and spatio-temporal correlation

Xuesong

2018

EURASIP J. Adv. Signal Process.

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“…Besides, another set of hand-crafted rules are derived to skip partial PUs to further reduce the complexity of the re-encoding part. Although it shows better performance than the aforementioned fast SCC encoder techniques [24]- [28], it still leaves large room for further improvement. Since only limited hand-crafted rules are derived in [29], it may not handle the complicated situation in SCC transcoding well.…”

Section: Introductionmentioning

confidence: 98%

“…To reduce the computational complexity of SCC bitrate transcoding, one solution is to replace the original SCC encoder in CBFT by various fast SCC encoders [24]- [28]. In [24], a fast CU size decision method was proposed for stationary CUs in screen content videos. All modes are searched if the depth level of the current stationary CU is equal to its collocated CU.…”

Section: Introductionmentioning

confidence: 99%

“…Although the complexity of the SCC encoder is reduced by these techniques, the reduction is still limited. First, the fast prediction rules in [24]- [28] rely on the assumption that the computer-generated SCBs are noisefree, but this assumption does not hold for decoded videos in the CBFT due to the lossy encoding and decoding. Second, they only utilize the information from the encoder side for computational complexity reduction but do not consider the information from the decoder side.…”

Section: Introductionmentioning

confidence: 99%

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Efficient Intra Bitrate Transcoding for Screen Content Coding Based on Convolutional Neural Network

Chan

Tsang

2019

IEEE Access

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The Screen Content Coding (SCC) extension of High Efficiency Video Coding (HEVC) is developed to improve the coding efficiency of screen content videos. To meet the diverse network requirement of different clients, bitrate transcoding for SCC is desired. This problem can be solved by a conventional brute-force transcoder (CBFT) which concatenates an original decoder and an original encoder. However, it induces high computational complexity associated with the re-encoding part of CBFT. This paper presents a convolutional neural network based bitrate transcoder (CNN-BRT) for SCC. By utilizing information from both the decoder side and the encoder side, CNN-BRT makes a fast prediction for all coding units (CUs) of a coding tree unit (CTU) in a single test. At the decoder side, decoded optimal mode maps that reflect the optimal modes and CU partitions in a CTU is derived. At the encoder side, the raw samples in a CTU are collected. Then, they are fed to CNN-BRT to make a fast prediction. To imitate the optimal mode selection in the original re-encoding part, CNN-BRT involves a loss function that takes both of the sub-optimal modes and the final optimal modes into consideration. Compared with the HEVC-SCC reference software SCM-3.0, the proposed CNN-BRT reduces encoding time by 54.86% on average with a negligible Bjøntegaard delta bitrate increase of 1.01% under all-intra configuration. INDEX TERMS Transcoding, screen content coding (SCC), fast algorithm, convolutional neural network.

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Optimal sequence reordering for low delay screen content coding

Shi

Wang

et al. 2023

Multimed Tools Appl

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Fast intra mode decision and block matching for HEVC screen content compression

Cited by 25 publications

References 10 publications

A fast HEVC intra-coding algorithm based on texture homogeneity and spatio-temporal correlation

A fast HEVC intra-coding algorithm based on texture homogeneity and spatio-temporal correlation

Efficient Intra Bitrate Transcoding for Screen Content Coding Based on Convolutional Neural Network

Optimal sequence reordering for low delay screen content coding

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