1 October 1997 Spatiotemporal segmentation based on two-dimensional spatiotemporal entropic thresholding
Author Affiliations +
Optical Engineering, 36(10), (1997). doi:10.1117/1.601512
A novel spatiotemporal segmentation technique is further developed for extracting uncovered background and moving objects from the image sequences, then the following motion estimation is performed only on the regions corresponding to moving objects. The frame difference contrast (FCON) and local variance contrast (LCON), which are related to the temporal and spatial homogeneity of the image sequence, are selected to form the 2-D spatiotemporal entropy. Then the spatial segmentation threshold is determined by maximizing the 2-D spatiotemporal entropy, and the temporal segmentation point is selected to minimize the complexity measure for image sequence coding. Since both temporal and spatial correlation of an image sequence are exploited, this proposed spatiotemporal segmentation technique can further be used to determine the positions of reference frames adaptively, hence resulting in a low bit rate. Experimental results show that this segmentation-based coding scheme is more efficient than usual fixed-size coding algorithms.
Jianping Fan, Liming Zhang, Fuxi Gan, "Spatiotemporal segmentation based on two-dimensional spatiotemporal entropic thresholding," Optical Engineering 36(10), (1 October 1997). http://dx.doi.org/10.1117/1.601512

Image segmentation

Image compression

Motion estimation

Signal to noise ratio

Gallium nitride


Image processing algorithms and systems

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