A methodology for calibrating multispectral IRS Wide-Field Sensors (WiFS), which cover typically about 700 km swath is suggested. Two available bands B3 and B4 of IRS-1C and -1D WIFS and respective bands from four of IRS-P6 Advanced WiFS (AWiFS) are employed. Data products acquired over the Thar Desert within 5 days (near-synchronous condition) were utilized. Linear regression model is assumed valid to obtain the calibration coefficients (CCs), after compensating for intrinsic variations of these bands due to spectral response functions and solar zenith angles. It is found that IRS-1C and -1D WIFS cameras show a strong linearity relationship, as evident from their data samples with goodness of fit of better than 0.99. The application of the CCs may hence provide the desired integrated information when their data products are used in tandem. Analysis of the IRS-P6 AWIFS and IRS-1D WIFS image pairs, however, shows a large variability in their output, especially for the Band B4 datasets. The CCs derived for these sensors' pair needs to be used cautiously, Variation in their relative spectral responses demands further investigation, probably with inclusion of the in-situ measurements to account for variations of the target reflectance and the atmosphere while attempting cross-calibration analysis.
With ever increasing demand for high spatial and spectral resolutions, high number of bits of multispectral (MS) sensor
imagery from space borne systems, but not compensated by an equivalent increase on onboard data transmission or
memory limits, efficient data compression and/or streaming approaches gain importance. This paper discusses about the
use of JPEG-Like algorithm, for which hardware and software were well proven from the Cartosat-1 spacecraft, to
compress onboard high resolution multispectral imagery for future missions. It studies two possible ways of
compressing the multispectral data: (1). Apply JPEG-like algorithm bandwise for all three bands, and decompress in
ground processing. This would yield compression ratio (CR) of 1:3.31, (2). Combine IRS-Green and Red (since both are
highly correlated bands) in quincunx sampling grid, compress the grid and IRS-NIR data by JPEG algorithm. This
approach would have the advantage of a higher CR of 1:4.97. It was found that the JPEG like algorithm used in
Cartosat-1 could be directly used for MS data onboard as it would still preserve the spatial and spectral contents of the
multispectral information after decompression in ground processing. Further research work is required to improve the
image quality in the latter case despite the fact that it offers a better CR.
This paper investigates the estimation of modulation transfer function (MTF) and point spread function (PSF) using onorbit
data of the first dedicated cartographic mission of ISRO, namely, IRS-Cartosat-1. The Cartosat-1 was launched in
May 2005 with a motivation to realize in-track stereo-pair imagery at a ground sampling distance of 2.5 m with one of
its two cameras, AFT, kept to view a ground scene at -5o and the other, FORE, at +26o with respect to nadir. As with
any high-resolution satellite imagery, several factors viz., stray light, optics aberrations, defocusing, satellite motion,
atmospheric transmittance etc. can have a strong impact on the observed spatial quality of the Cartosat-1 imagery. These
factors are cumulatively accounted by PSF or by the MTF in the spatial frequency domain. The MTF is, thus, of
fundamental importance since it provides assessment of spatial response of the overall imaging performance of the
system. In this paper, estimation of the PSF and MTF was carried out by capturing imagery over airport runway strip as
well as artificial targets laid at two different locations within India. The method adapted here uses a sharp edge from two
adjacent uniform dark and bright fields or targets. A super-resolved edge of sub-pixel resolution was constructed from
the image edge slanted to satellite path to meet the basic requirement that the target width is much smaller than the
spatial resolution width. From the preliminary results, the MTF for the FORE is found to be approximately lesser by
about 2% with respect to AFT; this difference may be attributed to relatively a longer traverse of ground signal through
the atmospheric column in the case of FORE camera.
With ever-increasing number of spectral channels from space-borne hyperspectral instruments, demand on approaches
for fast search schemes for matching hyperspectral pixel vector with standard spectral library database has increased
proportionately. The present-day methods are tedious and time consuming to meet the above task. We propose a fast
matching scheme based on bivariate short-interval local variance that can be used to capture the essence of reference
materials in the spectral library. The variance of each selected window is computed across the spectral curve data and
the peak variance above a threshold is taken as a spike. The position and linewidth of the spikes are shown to carry
unique signatures of the given material spectral data, which can be stored and used as matching criteria. The choice of
appropriate threshold is important; it has been found that the mean value of background variance signal could be used as
the threshold value. The proposed method was successfully applied to identify some samples of the AVIRIS
hyperspectral imagery to the standard JPL spectral library database.
This paper presents three approaches to the problem of obtaining the left ventricular boundaries from cardiac MR data. The first presents a new model based approach for the detection of the endocardium from 4D MR cardiac images. The method proposed here links shape modeling and edge detection to provide a compact representation of the endocardium. A spatio-temporal edge detector has been designed to incorporate the temporal information available in 4D images. This edge detector has a stronger response to dynamic edges than static edges. Since the ventricle is a dynamic shape, boundaries detected using this edge detector are far better than those detected using a spatial edge detector. The output of our edge detector is iteratively corrected using a spherical harmonic model. This model based approach allows us to overcome the problems of noise and missing boundary information. Our system is fully automated and its output consists of the extracted boundary in each slice and a 3D surface model for each time instant. Quantitative evaluation is done by comparing the results of the algorithm with manually extracted ground truth for 12 data sets. The second approach uses filters applied across the detected tag lines to remove the tags from SPAMM-tagged MR data to allow existing boundary detection algorithms to function with minimal changes. The third approach uses the Fuzzy c-Spherical Shell algorithm directly on tagged (and untagged) data to determine the approximate LV center.
In this paper, we present a new approach for the automatic tracking of SPAMM (Spatial Modulation of Magnetization) grid in Cardiac MR images and consequent estimation of deformation parameters. The tracking is utilized to extract grid points from MR images and to establish correspondence between grid points in images taken at consecutive frames. These correspondences are used with a thin plate spline model to establish a mapping from one image to the next. This mapping is then used for motion and deformation estimation. Spatio- temporal tracking of SPAMM grid is achieved by using snakes--active contour models with an associated energy functional. We present a minimization strategy which is suitable for tracking the SPAMM grid. By continuously minimizing their energy functionals, the snakes lock on to and follow the in-slice motion and deformation of the SPAMM grid.
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