The design of any modern imaging system is the end result of many trade studies, each seeking to optimize image quality within real world constraints such as cost, schedule and overall risk. Image chain analysis -the prediction of image quality from fundamental design parameters -is an important part of this design process. At The Aerospace Corporation we have been using a variety of image chain analysis tools for many years, the Parameterized Image Chain Analysis & Simulation SOftware (PICASSO) among them. In this paper we describe our PICASSO tool, showing how, starting with a high quality input image and hypothetical design descriptions representative of the current state of the art in commercial imaging satellites, PICASSO can generate standard metrics of image quality in support of the decision processes of designers and program managers alike.
JPEG-2000 is the new image compression standard currently under development by ISOIIEC. Part I of this standard provides a "baseline" compression technology appropriate for grayscale and color imagery. Part II of the standard will provide extensions that allow for more advanced coding options, including the compression of multiple component imagery. Several different multiple component compression techniques are currently being investigated for inclusion in the JPEG-2000 standard. In this paper we apply some of these techniques toward the compression of HYDICE data. Two decorrelation techniques, 3D wavelet and Karhunen-Loeve Transform (KLT), were used along with two quantization techniques, scalar and trellis-coded (TCQ), to encode two HYDICE scenes at five different bit rates (4.0, 2.0, 1 .0, 0.5, 0.25 bits/pixel/band). The chosen decorrelation and quantization techniques span the range from the simplest to the most complex multiple component compression systems being considered for inclusion in JPEG-2000. This paper reports root-mean-square-error (RMSE) and peak signal-to-noise ratio (PSNR) metrics for the compressed data. A companion paper [1] that follows reports on the effects of these compression techniques on exploitation of the HYDICE scenes.
Environmental Data Records (EDR) from the Visible Infrared Imaging Radiometer Suite (VIIRS) have a need for Reflective Solar Band (RSB) calibration errors of less than 0.1%. Throughout the mission history of VIIRS, the overall instrument calibrated response scale factor (F factor) has been calculated with a manual process that uses data at least one week old and up to two weeks old until a new calibration Look Up Table (LUT) is put into operation. This one to two week lag routinely adds more than 0.1% calibration error. In this paper, we discuss trending the solar diffuser degradation (H factor), a key component of the F factor, improving H factor accuracy with improved bidirectional reflectance distribution function (BRDF) and attenuation screen LUTs , trending F factor, and how using RSB Automated Calibration (RSBAutoCal) will eliminate the lag and look-ahead extrapolation error.
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