Auto-detection of Heterogeneous Areas in Radiometric Normalization

Due to the difference in illumination condition, atmosphere condition, shooting angle and other inner and outer factors, there are differences in radiometry between different optical remote sensing images. The radiometric differences will affect the mosaic result and further affect some applications. To minimize such radiometric differences, radiometric normalization between images is a useful pre-processing step. However, there are often some heterogeneous areas in images. They are harmful to the radiometric normalization and even lead to the failure of the radiometric normalization. So it is necessary to detect these areas automatically. In order to achieve a more accurate result about the heterogeneous areas at the given scale, this paper based on the idea of SR (Super resolution) proposals an auto-detection method for heterogeneous areas using texture information. Then those heterogeneous areas are excluded during the generation of statistics for the radiometric normalization. Experiments indicate the approach proposed by this paper is feasible and the effect of radiometric normalization is also improved obviously. * Corresponding author. Jun Pan, Email: [email protected], Phone 86-27-68778969, Fax: 86-27-68778969.