Analysis of synthetic aperture radar image enchancement algorithm

Abstract

Most airborne and orbital SAR systems are monostatic, in that they employ a single antenna for transmission and reception of the radar signal. In optics, an imaging lens applies a phase function to a scattered field so that coherent summation occurs at the correct location in the image plane. Areas of current research and development include foliage penetration, ground penetration, imaging moving vehicles, bistatic imaging and techniques for improved image quality. Synthetic aperture radar imaging provides high resolution images of large areas. The intensities of pixels in a SAR image are based on the spatial orientation, roughness, and dielectric constant of the surface imaged. SAR is an active sensor, transmitting its own energy, and then measuring the return scattered by the earth's surface back to the satellite's antenna. SAR processing is the transformation of raw SAR signal data into a spatial image Due to the imaging mechanism, Synthetic Aperture Radar (SAR) images are susceptible to speckle noise, which affects radar image interpretation. So image enhancement is important topic of improves SAR image clarity. A nonlinear image enhancement algorithm based on nonsubsampled contourlet transform (NSCT) is proposed in this paper. The image is decomposed into coefficients of different scales and directions through nonsubsampled contourlet transform. It is denoised by the threshold method of the multi-scale product of NSCT coefficients. Then thresholds of the nonlinear enhancement function are determined according to the coefficients of each scale. The two parameters of the function, among which one is used to control the range of enhancement and the other can determine the strength of enhancement, are obtained by solving nonlinear equations. The coefficients processed by the enhancement function are used to reconstruct the image. The simulation results on the Matlab platform show that the algorithm has a good effect of enhancing details of images and suppressing noise signals meanwhile.