Highly scalable video compression with scalable motion coding

Abstract

A scalable video coder cannot be equally efficient over a wide range of bit rates unless both the video data and the motion information are scalable. We propose a wavelet-based, highly scalable video compression scheme with rate-scalable motion coding. The proposed method involves the construction of quality layers for the coded sample data and a separate set of quality layers for the coded motion parameters. When the motion layers are truncated, the decoder receives a quantized version of the motion parameters used to code the sample data. The effect of motion parameter quantization on the reconstructed video distortion is described by a linear model. The optimal tradeoff between the motion and subband bit rates is determined after compression. We propose two methods to determine the optimal tradeoff, one of which explicitly utilizes the linear model. This method performs comparably to a brute force search method, reinforcing the validity of the linear model itself. Experimental results indicate that the cost of scalability is small. In addition, considerable performance improvements are observed at low bit rates, relative to lossless coding of the motion information.

Direction-Adaptive Discrete Wavelet Transform for Image Compression

“…In [29], we have also developed an approach to allow lossy coding of the selections in order to provide a scalable direction representation, analogous to the scalable representation of motion vectors in video coding [30], [31].…”

“…As an example, assume that the prototype 1-D prediction filter has impulse response is even is odd (30) and, hence, . In addition, assume that the prototype 1-D update filter has impulse response .…”

Concept of Integrating Real Time Field Images in Computer in Process Industries by Removing Separate TVs

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Graph-Based Representation for Multiview Image Geometry

“…We note that methods that consist in coding directly the depth maps are in fact performing quantization of the depth vectors. Yet, in the similar context of video coding, direct quantization of motion information has been considered [14], [15] but is in general not used. By analogy, we argue that quantization of depth maps is not the most efficient to code this information, even if smart RD optimization criteria are used [12], [13], [16]- [20].…”