A fast and robust cirrus removal method for Landsat 8/9 images

Abstract

High-quality cirrus removal plays a crucial role in remote sensing data analysis. Cirrus parallaxes are commonly observed within the vicinity of cirrus clouds in the visible and near-infrared (VNIR) bands of Landsat 8/9 images. Cirrus parallaxes have a nonnegligible effect on cirrus removal, but the existing methods do not account for the correction of parallaxes. Meanwhile, large-scale image processing involves intensive computation that requires extensive computing time. To address the effect of cirrus parallaxes and the low processing efficiency, we propose a fast and robust cirrus removal (FRCR) method. FRCR has achieved the first realization of the statistics law of cirrus parallax between the VNIR and cirrus bands, thus realizing the cirrus parallax correction. In addition, FRCR introduces an automatic sampling method to obtain the regression samples for practicality. Then, a Compute Unified Device Architecture (CUDA) based Newton method with constraints is introduced to parallelize the computation, to improve the computational performance. Experiment results of various scenarios demonstrate that the FRCR method can achieve high-quality cirrus removal by eliminating cirrus parallaxes, and significantly improving computational performance.