Multispectral CIR image calibration for cloud shadow and soil background influence using intensity normalization

The effect of variable illumination and soil background in remotely sensed images is a major concern in the application of remote sensing in precision agriculture. Two band ratios, intensity-normalization and NDVI, were tested on a CIR image acquired under partially cloudy conditions, to eliminate the effect of variable illumination caused by cloud shadow. The intensity-normalization method was also compared with NDVI, SAVI, and OSAVI for soil background adjustment. As expected, the three intensity-normalized images and NDVI successfully eliminated the effect of variable illumination caused by cloud shadow. Although intensity-normalized bands, NDVI, SAVI, and OSAVI slightly reduced the influence of soil background in the CIR images, all six indices showed significant difference between at least two of the three soils during the early growing season when there was significant soil background contribution in the image.