Title :
Attention choice on quotient space composition for automatic target image segmentation
Author_Institution :
Inst. of Remote Sensing & Inf. Eng., Wuhan Tech. Univ. of Survey & Mapping, China
Abstract :
The authors present a novel method for image segmentation using neocognitron neuron model with diffusion and concentration properties controlled by quotient structure. The contributions of this paper are two fold: (1) In order to remark upon the relationship between the components of an image corresponding to the patches, which give the typed association of objects, the notion of quotient space composition and projection is introduced. This provides the advantage that the new patches for image segmentation may be created by merging the patches from the above level of the quotient space. (2) The hierarchical structure of neocognitron for the attention choice is adjusted with the variance of scenes by the process of the diffusion and concentration. The validity of our approach is demonstrated by an example in image analysis
Keywords :
geophysical signal processing; geophysical techniques; geophysics computing; image segmentation; neural nets; remote sensing; terrain mapping; algorithm; attention choice; automatic target image segmentation; concentration properties; diffusion; geophysical measurement technique; hierarchical structure; image processing; image segmentation; land surface; neocognitron; neocognitron neuron model; neural net; patch; projection; quotient space composition; quotient structure; radar remote sensing; remote sensing; terrain mapping; Automatic control; Image analysis; Image segmentation; Image storage; Information processing; Layout; Merging; Neurons; Predictive models; Remote sensing;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000. IEEE 2000 International
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-6359-0
DOI :
10.1109/IGARSS.2000.861665