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68 3. Standard destriping techniques and application to MODIS of the selected wavelet. If the analysing wavelet has enough vanishing moments, regular areas will have small wavelet coefficients and the stripe noise will be isolated in the highest resolution scales (figure 3.17b). On the contrary, if the number of vanishing moments is weak, stripe noise will also affect wavelet coefficients of lower resolutions (figure 3.17a) and therefore, wavelet destriping provides images with a weak ID index. The facet filtering model proposed in [Rakwatin et al., 2007] is used over the histogram matching techniques to process random stripes. Due to its hybrid aspect, it is not compared to other techniques. Filtering techniques provide results that are visually better than equalization methods because the removal of stripes can be tuned with σ for band-pass frequency filtering or m for wavelet thresholding. However, blurring and ringing artifacts introduced in the corrected signal discards any further quantitative analysis based on radiometric values. The limitations of standard techniques exposed in this chapter serve as a basis for the development of a robust destriping technique. An optimal destriping algorithm should satisfy the following requirements : - Complete removal of stripe noise, whether periodic or random - Minimization of the distortion introduced in the restored image From the definition of the NR and ID indexes, an optimal destriping algorithm increases NR while leaving ID close to 1. To achieve such results, we explore in the next chapter the striping issue from a variational perspective.
Figure 3.18 – Destriped results on Terra MODIS band 30 (TL) Original image (TC) Moment matching (CL) Histogram matching (CR) IFOV method (BL) Frequency filtering (BR) Wavelet thresholding. Reflectances over oceanic regions are highlighted to emphasize the presence of residual stripes. 69
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École Doctorale d’Informatique,
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5 Résumé Nou abordons dans cette
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8 TABLE DES MATIÈRES 3.5 Frequency
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10 TABLE DES MATIÈRES
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12 1. Introduction A common issue f
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14 1. Introduction
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16 2. Remote Sensing with MODIS In
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118 5. Application : Restoration of
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- Alaska Labrador Siberia Restorati
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128 Conclusion
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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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