Compression of SAR images using KLT, VQ and mixtureof principal components
R.D. Dony, S. Haykin · IEE Proceedings - Radar Sonar and Navigation · 1997
Owing to the very high-resolution nature of synthetic aperture radar (SAR), any use of image compression on such data must minimise the degree of distortion introduced. Two common methods for compressing images are linear block transform coding, such as the Karhunen–Loève transform, and vector quantisation. However, the implicit assumption of stationarity for these techniques is far from valid for most images. As a result, they introduce distortions in regions within an image that are significantly different from its global statistics. A new approach to data representation, referred to as the mixture of principal components (MPC), is proposed which combines advantages of both transform coding and vector quantisation. Like vector quantisation, it partitions the input space into a number of non-overlapping regions, and each region is represented by a number of basis vectors in the manner of transform coding. When applied to the compression of SAR images, the MPC method introduces less distortion for a given compression ratio compared with the other two techniques. For example, at 0.25 bits per pixel (a compression ratio of 64:1), the degree of distortion is reduced by close to 3 dB. When the resulting images are compared, the visibility of the distortion is also reduced when the new method is used.