A Semiphysical Approach of Haze Removal for Landsat Image

The presence of haze could seriously contaminate the observations optical satellite imagery. Haze not only significantly affects visual interpretation but also reduces accuracy map products. In this article, a semiphysical approach is proposed to reduce effects for Landsat image. based on physical model radiative transfer theory and dark objects. As depth remotely sensed image almost constant value, coarse transmission atmosphere estimated by thickness, other than scene map. derived utilized correct color shift induced airlight. For veiled textural information, guided-filter adopted refine restore information. Experiments are conducted upon images acquired at different dates spatial locations. dehazed results suggests that generate visually promising preserve spectral properties land surfaces. Moreover, it performs favorably against several state-of-the-art deep learning methods classic algorithm. quantitative assessments demonstrate developed enhance information with minimum spectrum changes. With assessments, we can conclude solution dehazing. It expected improve data quality hazy expand usability data.