Radiometric correction in remote sensing refers to the process of adjusting the brightness and contrast of an image to make it consistent with the real-world conditions under which it was acquired. This correction is necessary because the sensors used in remote sensing can be affected by factors such as atmospheric conditions, sun angle, and sensor noise, which can result in variations in the brightness and contrast of the image.
The main goal of radiometric correction is to remove these variations and make the image more representative of the real-world conditions. This is done by using mathematical algorithms and models to adjust the brightness and contrast of the image based on various factors such as the sun angle, atmospheric conditions, and sensor noise.
There are several different methods used for radiometric correction, including atmospheric correction, sensor correction, and image enhancement. Each method is used to correct a specific type of variation in the image. For example, atmospheric correction is used to remove the effects of atmospheric scattering and absorption on the image, while sensor correction is used to remove the effects of sensor noise.
Overall, radiometric correction is an essential step in remote sensing, as it allows us to produce accurate and reliable images that can be used for a wide range of applications, such as land use and land cover mapping, natural resource management, and environmental monitoring.
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