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Radiometric normalization of sensor scan angle effects in optical remote sensing imagery

Radiometric distortions along the scan line, caused mainly by the atmosphere, reflection properties of the imaged surface objects, and topography are observed frequently in images acquired by optical remote‐sensing sensors, especially airborne sensors with a wide field of view. In practical applications, such as classification or mosaicking of image data, a relative correction or normalization of these radiometric distortions is needed. Therefore, the goal of this paper is to derive a relative correction algorithm for multispectral line scanner images, which allows the spectral radiance values for different scan angles to be converted to radiance values of a defined reference scan angle. Under the simplifying assumption of complete diffuse reflectors, these radiometric distortions are modelled using a linear equation between the radiances of a pair of scan angles for each class of surface objects separately. A linear regression, applied to all these equations, results in a linear model for the radiance correction, a new empirical radiometric correction method, which is a generalization of earlier proposed strictly additive or multiplicative models. The proposed method is based solely on the digital image data. So, no additional information or user interaction is required, and the method is fully automatic. Applications for data acquired with the airborne multispectral scanner DAEDALUS AADS 1268 ATM show the effectiveness and potential of the proposed method especially for mosaicking and classification purposes.