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Imaging spectral technique is a new technology developed in 1980s. This technology is able to imagine the same object in the continuous spectral band by integrating the imaging technology and spectral technology, as well as optics, optoelectronics, electronics, information-processing and computer science and technology. With wide application of the Imaging Spectrometer, Images’ spatial, spectral and time-resolution become higher, which corresponding improves the spectrum data largely. So, to compress the great-capacity of data is becoming an urgent problem.Firstly, we summarize the development of the Imaging Spectrometer, the process of drawing the data-compression problem and the research status about abroad and home. Then, we introduce the development and some theories of image-compression, as the basic of the following contents.On the basic of the image relativity and entropy, the paper presents the characteristics of the hyper-spectral images in detail, and points out that those images not only have the distinct space relativity, but also enjoy the high spectral relativity, which differ from the general digital images. When analyzing the hyper-spectral image’s entropy, we ascertain the floor level of the hyper-spectral image’s entropy, that is the least bit rate on the condition of Loss-less imaging compression.On the base of the relativities of space and spectra, and the characteristics of the entropy, we present three methods to express the hyper-spectral image serials, analyze the change of the relativity coefficient and entropy by different methods, and study the Loss-less compression method for hyper-spectral image. The technique usedSD2 PCM method to reduce spatial and spectral redundance of the images. The resultsprove that this arithmetic improves the Loss-less compression ratio, and it is quite simple, feasible and effective.
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