TARGET DETECTION USING MULTI-RESOLUTION ANALYSIS AND HOLDER CONSTANT

Through analyzing the different height parameter of 3D surface between the artificial target and complex background based on the description of average Holder constant of fractional Brownian motion, a novel method of target detection based on wavelet transformation and Holder constant is proposed. The wavelet Holder constants are calculated and linearly interpolated in a series of images, the target is detected by testing the linearity errof The more accurate localization can be achieved using two images of the same region but with difIerent scaling parameters.The application results of this algorithm for target detection are also given, and show that this method has good performance of noise immunity. This method is also suitable for identifying specific targets in complex background.

Through analyzing the different height parameter of 3D surface between the artificial target and complex background based on the description of average Holder constant of fractional Brownian motion, a novel method of target detection based on wavelet transformation and Holder constant is proposed. The wavelet Holder constants are calculated and linearly interpolated in a series of images, the target is detected by testing the linearity error. The more accurate localization can be achieved using two images of the same region but with different scaling parameters. The application results of this algorithm for target detection are also given, and show that this method has good performance of noise immunity. This method is also suitable for identifying specific targets in complex background.