A piece-wise approach to removing the nonlinear and irregular stripes in MODIS data

As a result of imaging acquisition conditions, Moderate Resolution Imaging Spectroradiometer (MODIS) imagery suffers from nonlinear and irregular striping. The nonlinear stripes are those whose degradation parameters change with the ground objects, and the irregular stripes are those in which only some of the pixels are contaminated. These kinds of stripes result in great difficulties for conventional statistical destriping methods. To deal with these problems effectively, we propose a piece-wise destriping method. This approach divides the recognized defective rows into different portions by the local statistical and mean curve information. The destriping is then performed in each portion, based on the different correction coefficients, with a neighbouring normal row as a reference. Experimental results demonstrate that the proposed algorithm can effectively destripe MODIS data.