Relative radiometric calibration for multispectral remote sensing imagery

Our environment has been changed continuously by nature causes or human activities. In order to identify what has been changed during certain time period, we need to spend enormous resources to collect all kinds of data and analyze them. With remote sensing images, change detection has become one efficient and inexpensive technique. It has wide applications including disaster management, agriculture analysis, environmental monitoring and military reconnaissance. To detect the changes between two remote sensing images collected at different time, radiometric calibration is one of the most important processes. Under the different weather and atmosphere conditions, even the same material might be resulting distinct radiance spectrum in two images. In this case, they will be misclassified as changes and false alarm rate will also increase. To achieve absolute calibration, i.e., to convert the radiance to reflectance spectrum, the information about the atmosphere condition or ground reference materials with known reflectance spectrum is needed but rarely available. In this paper, we present relative radiometric calibration methods which transform image pair into similar atmospheric effect instead of remove it in absolutely calibration, so that the information of atmosphere condition is not required. A SPOT image pair will be used for experiment to demonstrate the performance.