ARTIFICIAL TARGET RECOGNITION WITH MULTI-RESOLUTION ANALYSIS AND WAVELET HOLDER CONSTANT
结合多分辨分析和小波Holder数的人造目标识别方法

The average Holder constant of fractional Brownian motion is described, and the different relative distance between the target and complex background is extracted. It is good in noise immunity to use wavelet translation. The wavelet Holder constants which are linear interpolated are calculated in a serial of different multi resolution images, the target is recognized by detection of the linearity error. A novel algorithm of target recognition with multi resolution analysis and relative distance (MRRD) is proposed. Experiments show that this algorithm is suitable for identifying targets which are difficult to recognize in fractal feature parameter, and that it has simple computation and is convenient for real time processing.