Compression of Spectral Meteorological
نویسنده
چکیده
Data compression is essential to current low-earth-orbit spectral sensors with global coverage, e.g. meteorological sensors. Such sensors routinely produce in excess of 30 Gb of data per orbit ( over 4 Mb/s for about 110 min. ) while typically limited to less than 10 Gb of downlink capacity per orbit ( 15 minutes at 10 Mb/s ). Astro-Space Division develops spaceborne compression systems for compression ratios from as little as three to as much as twenty-twne for high--fidelity reconstructions. Current hardware production and development at AstrMpace Division focuses on discrete cosine transform ( DCT ) systems implemented with the GE PFFT chip, a 32x32 2D-DCT engine. Spectral relations in the data are exploited through block mean extraction followed by orthonormal transformation. The transformation produces blocks with spatial correlation that axe suitable for further compression with any block-oriented spatial compression system, e.g. AsthoSpace Division's Laplacian modeler and analytic encoder of DCT coefficients.
منابع مشابه
Compression of Spectral Meteorological I
Data compression is essential to current low-earth-orbit spectral sensors with global coverage, e.g. meteorological sensors. Such sensors routinely produce in excess of 30 Gb of data per orbit ( over 4 Mb/s for about 110 min. ) while typically limited to less than 10 Gb of downlink capacity per orbit ( 15 minutes at 10 Mb/s ). Astro-Space Division develops spaceborne compression systems for com...
متن کاملA Novel Color Image Compression Method Using Eigenimages
Since the birth of multi–spectral imaging techniques, there has been a tendency to consider and process this new type of data as a set of parallel gray–scale images, instead of an ensemble of an n–D realization. Although, even now, some researchers make the same assumption, it is proved that using vector geometries leads to better results. In this paper, first a method is prop...
متن کاملTowards Optimal Compression of Meteorological Data: A Case Study of Using Interval-Motivated Overestimators in Global Optimization
The existing image and data compression techniques try to minimize the mean square deviation between the original data f(x, y, z) and the compresseddecompressed data f̃(x, y, z). In many practical situations, reconstruction that only guaranteed mean square error over the data set is unacceptable. For example, if we use the meteorological data to plan a best trajectory for a plane, then what we r...
متن کاملSpectral/Spatial Hyperspectral Image Compression in Conjunction with Virtual Dimensionality
Hyperspectral image compression can be performed by either 3-D compression or spectral/spatial compression. It has been demonstrated that due to high spectral resolution hyperspectral image compression can be more effective if compression is carried out spectrally and spatially in two separate stages. One commonly used spectral/spatial compression implements principal components analysis (PCA) ...
متن کاملP10.11 Automatic Detection and Removal of Ground Clutter Contamination on Weather Radars
Radar backscatter from the ground can contaminate weather signals, often resulting in severely biased meteorological estimates. If not removed, these clutter returns tend to bias reflectivity high as well as Doppler velocity and spectrum width toward zero. A ground clutter filter (GCF) can mitigate this contamination and provide unbiased meteorological estimates but typically with reduced quali...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2009