JOURNAL ARTICLE

Complexity-aware adaptive bit-rate control with dynamic ROI pre-processing for scalable video coding

Abstract

We present a novel efficient complexity-aware adaptive bit rate control with dynamic Region-of-Interest pre-processing (pre-filtering) for the Scalable Video Coding (SVC), which is an extension of H.264/AVC. According to the proposed approach, we adaptively vary various parameters of the SVC pre-filters, such as standard deviations and a number of filters for the dynamic pre-processing of a transition region between the ROI and background, thereby enabling to dynamically adjust the desired SVC settings. Our adaptive bit-rate control 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 rate-distortion 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 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 both in quality and bit-rate.

Keywords:
Computer science Scalability Scalable Video Coding Region of interest Reference software Coding (social sciences) Computational complexity theory Real-time computing Encoding (memory) Computer hardware Artificial intelligence Software Algorithm

Metrics

13
Cited By
2.49
FWCI (Field Weighted Citation Impact)
11
Refs
0.90
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Video Coding and Compression Technologies
Physical Sciences →  Computer Science →  Signal Processing
Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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