Adaptive Edge Encoding Schemes for the Rate-Distortion Optimal Polygon-Based Shape Coding

Abstract

In this paper, we present two adaptive edge encoding schemes for the operational ratedistortion optimal polygon-based shape coding. The encoding edge is represented by an octant number, a major component, and a minor component, where the ranges of the two components are determined at two levels. For the object-level, these ranges are either determined by users or adaptive to the contour characteristics and the predefined admissible distortions using the discrete contour evolution method. For the edge-level, the range of the minor component is further adaptive to the magnitude of the major component. The appropriate code tables are selected for the two components according to their ranges. Experiments on MPEG-4 test sequences showed that our schemes outperform existing schemes in terms of bit-rate at the same distortion level.

Operationally optimal vertex-based shape coding with arbitrary direction edge encoding structures

“…27. Both consist of the sector number, the short component magnitude, and the long component magnitude, which are encoded with the optimal code words under two probability distribution assumptions.…”

Context Tree-Based Image Contour Coding Using a Geometric Prior

“…Another distortion metric is MADD, which measures the maximum distortion between the original and approximated contours. MADD is suitable for applications where perceptual quality is evaluated [11,12,45]. Consider for example a long contour with all edges shifted to the left by one pixel.…”

“…Experimental results show that for lossless contour coding, our proposed algorithm outperforms arXiv:1604.08001v1 [cs.MM] 27 Apr 2016 state-of-the-art context-based schemes [7,13] consistently for both small and large training datasets. For lossy contour coding, our algorithms outperform comparable schemes in the literature [9,12] in rate-distortion (RD) performance. Towards the goal of reproducible research [20], we have made the source code for lossless contour coding publicly available 1 .…”

“…However, the shape coding techniques developed to represent boundaries of objects [9]-called video object planes (VOP)-were not efficient enough, resulting in large SI overhead that rendered OBVC uncompetitive in compression performance. Some contemporary interest in the problem has shifted to lossy contour coding, where curve-and spline-based approximations are used [10][11][12].…”

“…f (w) is the cost of end node w on T . We minimize (12) recursively by dividing the original problem into sub-problems. The sub-problem is to minimize the end node cost F (T 0 u ) of a sub-tree T 0 u rooted at node u.…”