Key points are not available for this paper at this time.
Over recent years, miniaturized multispectral cameras mounted on an unmanned aerial vehicle (UAV) have been widely used in remote sensing. Most of these cameras are integrated with low-cost, image-frame complementary metal-oxide semiconductor (CMOS) sensors. Compared to the typical charged coupled device (CCD) sensors or linear array sensors, consumer-grade CMOS sensors have the disadvantages of low responsivity, higher noise, and non-uniformity of pixels, which make it difficult to accurately detect optical radiation. Therefore, comprehensive radiometric calibration is crucial for quantitative remote sensing and comparison of temporal data using such sensors. In this study, we examine three procedures of radiometric calibration: relative radiometric calibration, normalization, and absolute radiometric calibration. The complex features of dark current noise, vignetting effect, and non-uniformity of detector response are analyzed. Further, appropriate procedures are used to derive the lookup table (LUT) of correction factors for these features. Subsequently, an absolute calibration coefficient based on an empirical model is used to convert the digital number (DN) of images to radiance unit. Due to the radiometric calibration, the DNs of targets observed in the image are more consistent than before calibration. Compared to the method provided by the manufacturer of the sensor, LUTs facilitate much better radiometric calibration. The root mean square error (RMSE) of measured reflectance in each band (475, 560, 668, 717, and 840 nm) are 2.30%, 2.87%, 3.66%, 3.98%, and 4.70% respectively.
Cao et al. (Tue,) studied this question.