AIRBORNE SAR IMAGE BRIGHTNESS COMPENSATION ENHANCEMENT PROCESSING BASED ON NSCT TRANSFORM

Abstract

Image brightness compensation processing is one of the important aspects to decide whether the image can be further used for remote sensing quantitative applications. In this paper, a brightness compensation enhancement processing method based on nonsubsampled contourlet transform (NSCT) is used to address the widely used problems of synthetic aperture radar (SAR) images with unbalanced internal brightness and blurred detailed texture features and severe image SAR. Firstly, the image is decomposed using the NSCT transform and the sub-band coefficients are adjusted after calculating the improvement coefficients for the statistical radiation change curve of its low-frequency sub-bands to achieve brightness compensation; for each high-frequency sub-band image, a hard threshold function is used to enhance the contour texture information of the image and suppress noise; finally, all sub-bands are combined using NSCT inverse reconstruction to obtain the resultant image. Aiming at the problem of radiation discrepancies arising from SAR images due to its side-view observation method and antenna directional map, this method is more applicable to SAR images and has better improvement effects than the traditional image equalization algorithm, increasing the average gradient and structural similarity, better preserving the detail features, significantly improving the brightness non-uniformity problem, enhancing the visual effect and providing some support for the subsequent monitoring of various disasters.