Multiple-detector scanning systems exhibit striping patterns caused by non-uniform calibration and analog-to-digital quantization process. Traditional nonlinear destriping is based on cumulative histogram normalization of intraband detectors to their composite statistics for the total image. A new statistical procedure uses the fractional part of the floating point values derived by applying a destripingfunction to the data as a location address in a two-dimensional randomly generated binary table.1 This table controls the conversion from floating point to integer output, and replaces the traditional truncation conversion method. Because nonlinear destriping creates an integer look-up table for the normalization process, and intermediate floating point values are not created, revision of the traditional nonlinear destriping algorithm is necessary to incorporate the statistical procedure. Landsat multispectral scanner data acquired on June 2, 1973, were processed with both the traditional and revised nonlinear destriping techniques. Based on quantitative results, the revised destriping was preferred to the traditional destriping. However, within certain image structures the traditional destriping was qualitatively more successful. These results suggested that a different algorithm for traditional nonlinear destriping and another way of incorporating Bernstein's procedure could create a more acceptable and consistent product.
Mary E. Richards, Mary E. Richards,
"A Comparison Of Two Nonlinear Destriping Procedures", Proc. SPIE 0534, Architectures and Algorithms for Digital Image Processing II, (11 July 1985); doi: 10.1117/12.946572; https://doi.org/10.1117/12.946572