Magnitude image compression

Abstract

Embodiments of the invention view image intensity data as a spectrum of underlying wave forms. The spectrum of these waves can be approximated using spectral estimation techniques where the spectrum parameters constitute the compressed image. The image's underlying wave forms can be recovered using an inverse Fourier transform. The original image can also be symmetrically extended prior to the transform to preserve real valued transformed data and model parameters. The modeling method is typically based on a linear predictive methodology to obtain the spectrum parameters. Other transforms include a 2-D Fourier transform that transforms the image into a holographic representation similar to synthetic aperture radar (SAR) phase history. This 2-D waveform holographic format can be decorrelated into 1-D planar waves by applying a 1D Fourier transform. This process enables 1-D linear predictive modeling to obtain the spectral parameters. For compression applications the model parameters are preferably quantized.