Satellite sensors produce enormous data volumes, especially hyperspectral sensors that acquire over hundreds of images of narrow-wavelength bands and produce an image cube. Thus, a lot of effort has been made to study moreefficient ways to compress satellite images or image cubes. Compression techniques can be classified into three types: 1. Lossless compression, 2. Near-lossless compression, and 3. Lossy compression. Lossless compression techniques are reversible techniques that compress an image without loss of information. The reconstructed image is identical to the original image. Because there is no loss of information, this kind of compression technique is used for applications that cannot tolerate any difference between the original and reconstructed data. However, a lossless compression technique cannot achieve a high compression ratio, depending on the redundancy of the images. The larger the redundancy is, the higher the compression ratio that can be achieved. For optical satellite images, the lossless compression ratio is normally less than 3:1. For an image with a very smooth scene or extremely low spatial or spectral information in the data, a higher compression ratio may be achieved.