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48 3. Standard destriping techniques and application to MODIS Figure 3.6 – (Left) Noisy image from Terra MODIS band 27 (Right) Image destriped with histogram matching (IMAPP) used to establish the 8 detectors normalization curves. The look-up table was then successfully applied to destripe an independent image collected two weeks later on June 1, 1988. More recently, this approach was adopted by [Xiaoxiang et al., 2007] for the destriping of CMODIS (SZ-3 Chinese MODIS) data. It is currently implemented in the NASA IMAPP (International MODIS/AIRS Processing Package) software and distributed by the university of Madison-Wisconsin for MODIS users (http ://cimss.ssec.wisc.edu/imapp/). Additional features specific to MODIS data have been included in the software. Two sets of look-up tables were developed for both Terra and Aqua MODIS, and their application depends on the acquisition date of images to be detriped. The comparative study of section 3.8 uses the histogram matching technique implemented in the NASA IMAPP software. 3.4 Overlapping Field-of-View Method The Overlapping Field-of-View method (OFOV) was specifically designed for MODIS. Its basic principle was introduced by [Antonelli et al., 2004] and recently examined by [di Bisceglie et al., 2009]. This technique relies on another artifact of MODIS, the bowtie effect. When the scan angle of the mirror increases, the actual resolution of pixels also increases due to the earth curvature. The nominal resolution of a pixel is 1 × 1 km at Nadir and reaches 4.8 × 2km at the begining and ending of every scan, which correspond to scan angles of ±55˚. As a result of pixel resolution growth, a swath will cover an extended area of 20km along track at scan extremums, causing overlaps with previous and next swaths (figure 3.7a). Areas affected with the bowtie effect will display identical
49 Figure 3.7 – (Left) Bowtie effect due to the growth of pixel size in the cross track direction of a swath (Right) Image from Terra MODIS band 17, extracted from an area with a scan angle raging from 47˚ to 55˚. Bowtie effect appears as overlapping fields of view. geometrical features in successive scans. This is clearly visible along land/ocean transitions (figure 3.7b). The OFOV method then exploits the information redundancy to equalize the detectors responses. In the bowtie region (areas corresponding to scan angles higher than ±25˚), some of MODIS detectors are viewing exactly the same scene and, therefore thus deviations in the detectors reponses are only due to stripe noise. The OFOV algorithm is divided in two steps. Following the classification of the detectors as in-family and outof family detectors, a reference detector is selected and equalization functions are derived using only bow-tie measurements. The equalization curves are then applied to the detectors over the entire swath. To assess the accuracy of relative inter-detectors calibration, a Bowtie Based Detector Distance (BTBDD) between detectors i and j is defined as : d i,j = ∑ Ni,j n=1 |I i(n) − I j (n)| .W (n) ∑ Ni,j n=1 W (n) (3.11) where N i,j is the number of OFOVs of detectors i and j, with an overlapping percentage above η, a value fixed to 65%. I i (n) (respectively I j (n)) is the radiance measured by detector i (respectively j) on the n th OFOV and W (n) is the overlapping percentage. In addition to the BTBDD distances, the similarity between detectors ECDFs is computed using the Kolmogorov-Smirnov distance : D i,j = 1 N obs N obs ∑ |P i (r(n)) − P j (r(n))| (3.12) n
Page 1: École Doctorale d’Informatique,
Page 5: 5 Résumé Nou abordons dans cette
Page 8 and 9: 8 TABLE DES MATIÈRES 3.5 Frequency
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- Alaska Labrador Siberia Restorati
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130 BIBLIOGRAPHIE A. Chambolle. An
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132 BIBLIOGRAPHIE E. Hochberg, S. A
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134 BIBLIOGRAPHIE P. Perona and J.
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