Comparison of artificial and natural neural computation: an application to automatic target recognition

We make a few simple comparisons of the principles and performance for noise reduction and edge detection with conventional methods versus neural network methods. Noise reduction methods discussed include the wavelet packet transform. Edge detection is discussed from the point of view of the Sobel and Canny transforms. An approach using the IBM ZISC036 neural network chip is also discussed. In all cases, the results are compare to that of the biologically inspired PCNN. An application of the `best if both worlds' is demonstrated in a foveation/object isolation application for ATR.