Fuzzy c-means and singular value decomposition based through wall image enhancement

Singular value decomposition 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 c-means clustering algorithm. Moreover, weights are assigned to different singular values based on their membership value. Proposed scheme significantly works well for extracting multiple in heavy cluttered through wall images. Simulation results are compared on the basis mean square error, peak signal to noise ratio and visual inspection.