Adaptive Downsampling Video Coding With Spatially Scalable Rate-Distortion Modeling

Downsampling video coding, whereby downsampled frames are encoded, provides improved perceptual quality in rate-constrained situations. This method shows considerable advantages over other approaches, particularly in wide-spreading high-definition video formats. This paper provides a comprehensive analysis of downsampling video coding. The study proposes a spatially scalable rate-distortion (RD) model, comprising quantization-distortion and quantization-rate models, and develops an optimal encoding frame size determination framework. The proposed method achieves a gain up to 2.3 dB peak signal-to-noise ratio (PSNR) at 1 Mb/s when compared with conventional full frame size coding. The RD performance is close to the optimal scenario, in which the ideal frame size is obtained by heuristically performing downsampling coding in various allowable sizes.

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