The SAR Image Compression with Projection Pursuit Neural Networks

Abstract

Synthetic Aperture Radar (SAR) image compression is important in image transmission and archiving. We present a new algorithm for SAR image compression based on projection pursuit neural networks. At first, we segment an SAR image into regions of different sizes based on mean value in each region and then constructing a distinct code for each block by using the projection pursuit neural networks. The process is stopped when the desired error threshold is achieved. The experimental results show that excellent performance can be achieved for typical SAR images with no significant distortion introduced by image compression.