Radiometric normalization of optical remote sensing imagery

Sensor viewing effects, which are caused mainly by an atmosphere and a sun-sensor-target geometry, are observed quite often in images acquired by optical remote sensing sensors, especially airborne sensors with a wide field of view. We propose an image-based empirical radiometric normalization method, which is based on a linear regression applied over linear models between the observed radiance and the target radiance for each surface class separately. The experiments for data acquired by airborne multi-spectral scanner DAEDALUS AADS 1268 ATM show the effectiveness and potential of the proposed method especially for the mosaicking and classification applications