A SAR Image Denoising Method for Target Shadow Tracking Task

Abstract

The interpretation of Synthetic Aperture Radar (SAR) image is considered to be a challenging task, especially when tracking the target shadow in Video SAR (ViSAR), the speckle noise needs to be considered. Based on this, this paper proposes a SAR image denoising algorithm based on the improved wavelet threshold function. Different from the existing denoising methods, this algorithm combines the characteristics of hard threshold function and soft threshold function in traditional wavelet transform denoising, constructs a new threshold function, and improves the equivalent number of looks (ENL) of denoised SAR image. When the denoised image is applied to the tracking task, the target features are enhanced by k-means algorithm and binarization method, so as to improve the tracking accuracy. Experimental results show that the algorithm improves the tracking accuracy on the basis of ensuring the real-time performance of tracking and makes the tracking task highly robust to the noise of SAR image.