An image transform to characterize and compensate for spatial variations in thin cloud contamination of Landsat images

A haze optimized transformation (HOT) is developed and assessed for the detection and characterization of haze/cloud spatial distributions in Landsat scenes. The transformation is derived from an analysis of a visible-band space where spectral response to diverse surface cover classes under clear-sky conditions is highly correlated, but spectral response to haze is highly sensitive to both optical wavelength and haze optical depth. The robustness of the detection algorithm is demonstrated through its application to visible band imagery of seven Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) scenes that encompass diverse surface cover and atmospheric characteristics. A methodology for utilizing the transformed image to radiometrically compensate visible band imagery is presented and quantitatively tested in the correction of an example ETM+ scene.