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- W1999462241 abstract "A new parallel analytic data fusion method has been developed and tested on real image pairs. This fusion algorithm is based on the interaction between two analytically formulated constraints: (1) the principle of Knowledge Source Aggregation, and (2) the principle of Belief Enhancement/Withdrawal. In this paper, we discuss ways in which a message-passing multiprocessor employing the hypercube interconnection topology is exploited in order to achieve optimal speed-up in the parallel data fusion algorithm. Image parallelism is optimized by having multiple processors execute the same task but operate on different subsets of the data. Two numerical methods used to solve a system of partial differential equations resulting from the use of the Euler-Lagrange equation for the fusion process are compared. Tests conducted on an NCUBE/4 parallel computer have resulted in an effective implementation of the complete fusion process." @default.
- W1999462241 created "2016-06-24" @default.
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- W1999462241 date "1991-04-01" @default.
- W1999462241 modified "2023-09-23" @default.
- W1999462241 title "<title>Parallel data fusion on a hypercube multiprocessor</title>" @default.
- W1999462241 doi "https://doi.org/10.1117/12.25291" @default.
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