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The compression of multitemporal hyperspectral imagery is considered, wherein the encoder uses a reference image to effectuate temporal decorrelation for the coding of the current image. Both linear prediction and a spectral concatenation of images are explored to this end. Experimental results demonstrate that, when there are few changes between two images, the gain in rate-distortion performance is achieved over the independent coding of the current image. In addition, a strategy that explicitly removes salient temporal changes and stores them losslessly in the bitstream is proposed, and it is observed that this change-removal process results in a slight decrease in the rate-distortion performance with the benefit of perfect representation of the changed pixels.