Three-dimensional transform coding of multispectral data

We present a three-dimensional terrain-adaptive transform-based bandwidth compression technique for multispectral imagery. The transformation involves one dimensional Karhunen-Loeve transform (KLT) followed by two-dimensional discrete cosine transform. The algorithm exploits the inherent spectral and spatial correlations in the data. The images are spectrally decorrelated via the KLT to produce the eigen images. The resulting spectrally-decorrelated eigen images are then compressed using the JPEG algorithm. The algorithm is conveniently parameterized to accommodate reconstructed image fidelities ranging from near-lossless at about 5:1 compression ratio (CR) to visually lossy beginning at around 40:1 CR. A significant practical advantage of this approach is that it is leveraged on the standard and highly developed JPEG compression technology. Because of the significant compaction of the data resulting from the initial KLT process, an 8-bit JPEG can be used for coding the eigen images associated with 8, 10, or 12 bits multispectral data. The novelty of this technique lies in its unique capability to adaptively vary the characteristics of the spectral decorrelation transformation based upon the local terrain variation