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Adaptive frequency weighting for fine-granularity-scalability

To compensate for the unpredictability and variability in bandwidth between sender and receiver(s) over the Internet, a new scalable coding tool has recently been introduced in MPEG-4: Fine-Granularity-Scalability (FGS). The FGS framework is very flexible and can adapt in real-time to the Internet bandwidth variations by supporting both SNR and temporal scalability through a single pre-encoded fine-granular stream. However, while FGS is very flexible, it has a lower coding efficiency than non-scalable MPEG-4 coding. To reduce this visual quality penalty at low and medium bit-rates, a subjective quality improvement tool has been introduced in MPEG-4, allowing the prioritized transmission of low frequency DCT coefficients that contribute more to the visual quality. This tool is termed Frequency Weighting (FW). In this paper, we propose a novel scene-characteristic-dependent adaptive FW method that considerably improves the visual quality of FGS at low bit-rates. First, a thorough analysis of the FGS enhancement layer is performed at various bit-rates. Based on this analysis, we concluded that for improved visual quality, different FW methods should be used depending on the video sequence characteristics. Subsequently, we developed an automatic FW matrix adaptation mechanism that measures the brightness, motion and texture activity of each sequence and selects an appropriate FW method for that sequence from a set of a priori determined FW classes. This adaptive FW method has been subjectively evaluated and showed a clear improvement in visual quality compared with non-frequency weighted or non-adaptive frequency weighted sequences.