Destriping MODIS Data Using Overlapping Field-of-View Method

Multispectral sensors using array of detectors are affected by striping, an artifact that appears as a series of horizontal bright or dark periodic lines in the remotely sensed images. Nonlinearities and memory effect of detectors are the main causes of the striping problem that is not effectively corrected in the onboard or postprocessing calibration phases. In order to clear striping from images, we consider a new procedure based on detector response equalization and apply it to Moderate Resolution Imaging Spectroradiometer data from Terra and Aqua satellites. After identification of the out-of-family detectors, a least squares equalization stage is considered for calibration by using the intrinsic data redundancy caused by the hove-tie effect, where multiple observations of the same field of view are available from different detectors. The main advantage of this method, with respect to others such as the histogram equalization, is due to the independence of the measurements on the scene statistics, which, otherwise, will cause an overestimation or underestimation of the detectors' responses. The new procedure performance is validated using data received at the Mediterranean Agency for Remote Sensing and Environmental Control ground station facility in Benevento-Italy and data downloaded from NASA LAADS Web site. The main results are presented, by showing the effectiveness of the method and the stability of the correction coefficients, at least on one-orbit periods.