nuadon^
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m, in this paper,
ge were used to
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B4. Beijing 2008
moved properly, salt and pepper noise also can be effectively
restrained. On the whole, the algorithm we have designed is an
effective method for infrared image target detection.
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a 1 .single objective detection bl. multi-objective detec
tion c 1. salt and pepper noise detection
Figure 4.Result of detection
During the analysis of experiment result, occasionally the target
we got has small fracture in the center. It can be attributed to
the effect of the structure element’s shape which can’t fit to the
objective details. Fortunately, binary morphology opening and
closing operator are good at removing burrs and filling the
holes. The experiments have proved that this algorithm is effi
cient to detecting target in complex background images, and
can commendably meet the detection needs of different back
grounds or noised images.
6. CONCLUSION REMARKS
In this paper, the optimized genetic evolution model which
characteristic with the multi-strategy integration and parallel
evolutionary strategy is helpful to improve its premature con
vergence fault. Moreover the local explorative ability of the al
gorithm is enhanced obviously, as well as the algorithm’s effi
ciency and the results’ accuracy. Experimental results show that
the structure element which has been trained through GA does
contain the information of training samples. With the assistant
of those trained structure elements and morphology target de
tection method the complex natural background can be re-