PRINCIPLE COMPONENT ANALYSIS AND FUZZY LOGIC BASED THROUGH WALL IMAGE ENHANCEMENT

Principle component analysis based through wall image enhancement is proposed which is capable of discriminating target, noise and clutter signals. The overlapping boundaries of clutter, noise and target signals are separated using fuzzy logic. Fuzzy inference engine is used to assign weights to principle components. The proposed scheme works well significantly for extracting multiple targets having different range profiles in heavy cluttered through wall images. Simulation results are compared on the basis of mean square error, peak signal to noise ratio and visual inspection.