Haze removal based on advanced haze optimized transformation (AHOT) for multispectral imagery

Ever-present spatial varying haze contamination in satellite scenes limits applications using visible and near infrared bands of low temporal resolution multispectral satellite imageries. A relative atmospheric correction technique: virtual cloud point (VCP) based on advanced haze optimized transformation (AHOT) is developed for haze removal. It is an improved algorithm of the previous dark object subtraction (DOS) based on haze optimized transformation (HOT). In AHOT, extra steps are added to HOT to remove confusion caused by some land cover types. VCP uses not only lower bound but also upper bound of histogram, so it enlarges digital number (DN) variance reduced by haze, which is not considered in DOS. To evaluate this algorithm, hazy subsets of one Landsat TM and one QuickBird images are employed. Through before-and-after comparison using both true color images and NDVI, it proves that VCP based on AHOT is apparently better than DOS based on HOT, when haze is distributed over urban areas where vegetation is sparse.