.png){kind=icon}
Return
Joint Optimization of Transform and Quantization for High Efficiency Video Coding
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2019.2917260.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In high efficiency video coding (HEVC), transformation and quantization are separately performed to eliminate the perceptual redundancy of visual signals. However, a uniform quantizer can inevitably degrade the compression efficiency of fixed transform matrices due to varying space-frequency characteristics of video content. This paper introduces a joint optimization of transform and quantization approach for video coding. First, we compute a content dependent transform from the reconstructed reference by a fast Karhunen-Loeve transform (KLT). Second, using a template-based rate regularization, we jointly optimize transform and quantization (JOTQ) as a rate constrained optimization problem and obtain a feasible solution to improve coding performance. Finally, we design fast algorithms and early terminations to reduce the computational complexity of JOTQ. The experimental results show that JOTQ outperforms several previous methods by providing Bjontegaard Delta rate reductions of 4.11% and 3.38% on average under the low-delay and random-access configuration, respectively.
Keywords:
Video coding
content dependent transform
block adaptive quantization
high efficiency video coding (HEVC)
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.6
Papers:
9.8W
Citations:
29.4W
Organization
View more organizations
Cited Papers
ShareSaveTransverse and vortex domain wall structure in magnetic nanowires with uniaxial in-plane anisotropy
OAAI
OAAIShareSaveAn Improved Inter-Frame Prediction Algorithm for Video Coding Based on Fractal and H.264.png)
IEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAIShareSave View more