Discrimination of forests and man-made targets in SAR images based on spectrum analysis

In SAR images, the forests and man-made targets share a similar scattering power and scattering mechanism and they present a similar roughness or complexity in the local scale of images. However, it can be found that the canopy of forests has different degrees of pixel value changing on the small scale by image and scattering analysis. In this paper, spectrum analysis is employed to construct a novel method named Modified Spectrum Power to extract the differences and to discriminate forests and man-made targets. Fourier transformation is employed to acquire the frequency-matrix which represents the spectrum of pixels on the small scale and a weight-matrix is used to modify the amplitudes of components of different frequencies in the frequency-matrix aiming at enhancing the high-frequency component and weakening the low-frequency component. The summation of all elements in the modified frequency-matrix is defined as the Modified Spectrum Power. Based on the Modified Spectrum Power, forests can be discriminated from other targets with a high accuracy and man-made targets can be discriminated based on it. Experiments validate the ability of the Modified Spectrum Power on the discrimination between forests and man-made targets.