Embedded Transform Coding Based Lossless Compression in Compressive Spectral Imaging with Coded Aperture

Abstract

Summary form only given. The multi-shot Coded Aperture Snapshot Spectral Imaging system (CASSI) is an imaging architecture that senses the spectral imaging information of a 3D cube using a 2D focal plane array snapshot. Modeled as the summation of coded and shifted versions of different spectral voxels, the compressive CASSI measurements are difficult to be further compressed due to little correlation and redundancy. This paper is dedicated to retaining the correlations in the original data cube by an embedded transform coding on the compressive measurements. Through statistical modeling, the transformed measurements prove to be more approximate to the distribution of original spectral images than the compressive measurements. Meanwhile, bit-plane coding for the transformed measurements is applied by taking advantage of the known code aperture. The significant performance of this embedded coder on random compressive measurements is evaluated for different number of snapshots.