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Fast CU size and prediction mode decision method for HEVC encoder based on spatial features
- Source :
- Signal, Image and Video Processing. 10:1233-1240
- Publication Year :
- 2016
- Publisher :
- Springer Science and Business Media LLC, 2016.
-
Abstract
- In the high-efficiency video coding (HEVC) standard, intra prediction has higher computational complexity compared with H.264/AVC (advanced video coding) because of increasing the number of intra prediction modes and also higher number of coding unit (CU) sizes. The HEVC encoder evaluates 35 prediction modes on five possible prediction unit (PU) sizes to find the one with the minimum rate–distortion cost. Although this approach improves coding efficiency, it is very time-consuming. In this paper, we propose a fast intra prediction method to reduce the complexity of I-frame coding. The proposed method consists of three stages which is based on smoothness spatial feature. In the first stage, a measure is introduced to estimate CU smoothness by using sum of absolute differences (SAD) among CU pixels in four directions. By considering that a smooth region can be predicted with larger CUs, when the measured smoothness parameter is lower than a predefined threshold, only the prediction modes in the current CU are evaluated. In the second stage, the number of intra prediction modes is reduced based on the calculated SADs in the previous stage. In the last stage, if the first three candidate modes resulted from rough mode decision stage in the previous PU and the current PU are similar, then the best mode prediction of the previous PU is selected as the best candidate mode. Experimental results indicate that the proposed method can reduce the coding time on average to 43 % and maintain coding video quality, whereas bitrate increases negligibly (0.5 %).
- Subjects :
- Pixel
Computational complexity theory
Computer science
Real-time computing
020207 software engineering
02 engineering and technology
Video quality
Sum of absolute differences
Algorithmic efficiency
Signal Processing
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Electrical and Electronic Engineering
Decision model
Encoder
Algorithm
Coding (social sciences)
Subjects
Details
- ISSN :
- 18631711 and 18631703
- Volume :
- 10
- Database :
- OpenAIRE
- Journal :
- Signal, Image and Video Processing
- Accession number :
- edsair.doi...........7a750b1d814d051f4f91f42aea23d038