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HEVC/H.265 Intra Coding Based on the Human Visual System
- Source :
- IEEE Access, Vol 7, Pp 186587-186599 (2019)
- Publication Year :
- 2019
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2019.
-
Abstract
- High efficiency video coding (HEVC) is standard in the video compression field and performs well not only in video compression coding, but also in image compression. Regions of interest (ROIs) and just noticeable difference (JND), two human visual models, can accurately quantify human visual system (HVS) characteristics as pixel values. Using ROIs and JND to assist in evaluating image distortion can effectively reduce human visual redundancy and reflect authentic perceptual distortions. However, they are not readily applicable to the HEVC test model (HM) in the pixel domain. It is difficult to secure a suitable Lagrange multiplier $\lambda $ and quantization parameter (QP) for the JND model in particular. This paper proposes different solutions for the use of rate control (RC) or not where an appropriate $\lambda $ value is available for perceptual models. In RC, the proposed approach centers on a robust relationship between QP and achieved $\lambda $ . And we also established a bit allocation technique using the related $\lambda $ and expression for the RC model. Experimental results validate the rationality and effectiveness of the proposed method.
- Subjects :
- HEVC
General Computer Science
Computer science
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
02 engineering and technology
Redundancy (information theory)
Distortion
0202 electrical engineering, electronic engineering, information engineering
General Materials Science
Perceptual Distortion
Quantization (image processing)
Pixel
Quantization (signal processing)
ROI
General Engineering
020206 networking & telecommunications
QP
JND
Human visual system model
020201 artificial intelligence & image processing
bits allocation
lcsh:Electrical engineering. Electronics. Nuclear engineering
lcsh:TK1-9971
Algorithm
Lagrange multiplier λ
Data compression
Coding (social sciences)
Image compression
Subjects
Details
- ISSN :
- 21693536
- Volume :
- 7
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....f6c29acabedd2a3af5daaef22cf20f81