| Summary: | 碩士 === 元智大學 === 實業計劃研究所工學組 === 82 === A new scheme is developed to grab uncovered background infor-
mation. According to this scheme the uncovered background is
tra- nsmitted to the receiver to update the background memory
in visu- al communication. The uncovered background information
is obtained by using the uncovered background predictor(UBP),
which is then combined with the motion-compensating predictor(
MCP). The estimate of the move- ment for the MCP is obtained by
employing the block matching alg- orithm. In the encoding
procedure, the histogram of the gray lev- els is derived for
the implementation of the Huffman codes. For the UBP, the
hypothesis testing technique with Truncated sequential
probability ratio test(TSPRT) is employed to decide t- he
background or object information in a image scene. In the TSP-
RT, the likelihood ratio function is formed with the
probability density functions(PDFs) of the object and the
background, in whi- ch the PDFs are estimated via probabilistic
neural network(PNN). Then, the differential pulse code
modulation(DPCM) is employed f- or encoding based on the
original image and reconstructed on with UBP and MCP.
Experimental results illustrate that the developed scheme for
uncovered background video image coding can adaptively
discrimin- ate between the object and the background signals of
consecutive image frames more accurately than the existing
methods. Furtherm- ore, the discrimination algorithm can be
implemented by using the PNN architecture, with which the
scheme for speedy video image c- oding scheme can be developed.
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