Ofer Hadar

Senior Academic

Complexity-aware adaptive spatial pre-processing for ROI scalable video coding with dynamic transition region

Dan Grois, Ofer Hadar

We present a complexity-aware adaptive spatial preprocessing (pre-filtering) scheme for the efficient Region-of-Interest (ROI) Scalable Video Coding (SVC). According to the proposed approach, we adaptively vary various parameters of the SVC pre-filters, such as standard deviations, a number of filters for the dynamic pre-processing of a transition region between the ROI and background, etc., thereby enabling to dynamically adjust the desired SVC settings. In addition, our adaptive spatial pre-filtering system is based on an SVC computational complexity-rate-distortion (C-R-D) analysis, thereby adding a complexity dimension to the conventional Region-of-Interest SVC R-D analysis. As a result, the ROI SVC visual presentation quality is significantly improved, which can be especially useful for various resource-limited devices, such as mobile devices. The performance of the presented adaptive spatial ROI SVC pre-processing scheme is evaluated and tested in detail, further comparing it to the Joint Scalable Video Model reference software (JSVM 9.19) and demonstrating significant improvements.

Publication language English
Pages 741-744
Publication status Published - 01.12.2011
6116661

Keywords

H.264/AVC
ROI scalability
Regions-of-interest (ROI) video coding
Scalable Video Coding (SVC)
high-quality visual presentation
image/video coding
pre-processing/pre-filtering

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition
Signal Processing
Access to Document
10.1109/ICIP.2011.6116661
Other files and links
Link to publication in Scopus