Spatiotemporal segmentation based on two-dimensional spatiotemporal entropic thresholding


Autoria(s): Fan JP; Zhang LM; 干福熹
Data(s)

1997

Resumo

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. (C) 1997 Society of Photo-Optical Instrumentation Engineers.

Identificador

http://ir.siom.ac.cn/handle/181231/3727

http://www.irgrid.ac.cn/handle/1471x/11243

Idioma(s)

英语

Fonte

Fan JP;Zhang LM;干福熹.,Opt. Eng.,1997,36(10):2845-2851

Palavras-Chave #光存储 #segmentation #spatiotemporal entropic thresholding #coding complexity #human visual masking
Tipo

期刊论文