An In-orbit Real-time Approach Of Imagery Compression Based On Large Amounts Of Remote-sensing Data

Nowadays, the EOS (Earth Observation System) has been stepped into the fourth generation of high space resolution. As a result of the development of the remote-sensor's technology, the human being now obtains more and more large amount of remote-sensing data in both observing the earth and exploring the deep space. This situation then needs higher quality of data compression on-board. And there is a very big disparity in the domain of imagery compression in-orbit between our country's level and the advanced one in the world. Consequently it is having the important theory significance and practical value to study some an algorithm of imagery compression on satellite for huge remote-sensing data quantity and the its realizing approach.The characteristic of remote sensing imagery is that they contain large amounts of information, big entropy value and high pixel speed. These need that the technology of data compression can be able to provide high real-time capability, high reconstruction quality and big compression rate. With analysizing many kinds of domestic and foreign compression methods having been applied on satellites or other space devices, this article takes the concrete project as background, work out a new compression way which mainly comprises lifting DWT (Discrete Wavelet Transform), quantification of setting-zero interzone and MRLE (Modified Run Length Encoding). Additionally, an electronic hardware platform has been developed to implement the new algorithm. The platform's core is TMS320C6416 DSP, a high-end image processing chip.First, the theory of wavelet transform and multi-resolution analysis have been introduced, how to use lifting DWT has been stated, and some representative coding methods have been studied after the presentation of Shannon coding theory. These work theoretically prepares for the subsequent MRLE.Second, a compression algorithm, called XDM, has been designed, whose main goal is to possess good real-time capability. This algorithm is going to use D9/7 biorthogonal wavelet, lifting scheme, three stage decomposition, quantification of setting-zero interzone and MRLE coding method. Further more, the optimal...