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42 3. Standard destriping techniques and application to MODIS
Detector Terra Band 27 Terra Band 30 Terra Band 33
– Mean value Std deviation Mean value Std deviation Mean value Std deviation
d 1 12982 1043.6 16933 2441.9 23072 1660.9
d 2 12982 1043.6 16933 2441.4 23072 1660.9
d 3 12982 1043.7 16934 2442.5 23072 1661.1
d 4 12981 1043.7 16934 2442.1 23072 1661.3
d 5 12982 1043.9 16934 2442.1 23072 1661.6
d 6 12982 1043.9 16934 2442.1 23072 1661.0
d 7 12984 1044.1 16934 2442.0 23072 1661.0
d 8 12981 1044.0 16934 2442.0 23072 1660.9
d 9 12980 1044.0 16934 2442.0 23072 1660.9
d 10 12980 1043.9 16934 2442.0 23072 1660.6
Table 3.1 – Mean/standard deviation values (DN) of 10 detectors for Terra
MODIS bands 27, 30 and 33. The small statistical deviation between detectors
discredits the application of moment matching on MODIS data
The moment matching technique only rectifies first/second order statistics and as such
requires a careful selection of the reference signal. If a detector with strong statistical
deviations from others (a detector responsible for random stripes for exemple) is used
as a reference, moment matching can result in very poor destriping. Many strategies based
on the analysis of inter-detector response statistics can be used (see section 3.4). A
common option is to rely on mean/standard deviation values computed over the entire
scene. Altough the simplicity of its implementation makes it a popular technique, moment
matching suffers from many limitations described in [Horn and Woodham, 1979]. A major
issue pointed out on MSS is the impact of non-linearities in photomultipliers responses,
presumably abscent in more sophisticated imaging devices. Mean/standard deviation values
reported in tables 3.1, 3.2 and experiments conducted on both Terra and Aqua MODIS
data, illustrate how moment matching only results in partial destriping (figure 3.3). Indeed,
the gain/offset model only modifies the affine response of the detectors and fails to
take into account non-linear effects, highly responsible for residual stripes. Local analysis
of MODIS swaths reveals a dependency of detectors linear response to the signal intensity.
This can be verified experimentally by estimating gains/offsets from swaths covering
different levels of radiances (oceans and clouds). Furthermore, first order statistics make
the method very sensitive to the geophysical content of the images. In many cases, small
clouds or other highly reflective targets, are only visible by a limited set of detectors and
the resulting statistical bias is not accounted for in the moment matching procedure.
3.3 Histogram Matching
The hypothesis of linear and stationnary response exploited by the moment matching
method is too strong to provide reliable results on MODIS data. Investigation of
tables 3.1, 3.2 shows that on Terra/Aqua bands severely contaminated with stripes, detectors
have very similar mean/standard deviation values. The visual examination of su-