Image Correction Algorithms In Remote Sensing

With the development of modern remote sensing technology, more and more multi-resolution, multi-temporal and multi-spectral remote sensing image data are provided by different kinds of remote sensors. It is urgent for us to find a way to synthesize different kinds of image data.This paper firstly introduces the basic theory and method of remote sensing image correction. Then the correction of remote sensing image preprocessing, including remote sensing image system-level calibration, is inclined to range display to geometric correction and radiometric correction of remote sensing image. Then discussed image correction algorithm based on the ground control point. And analysis infection of the calibration accuracy comes from the control points, according to the character of the algorithm. In view of the results, give out the automatic selection algorithm and selection algorithm. Give out the theory of remote sensing image correction bases on interpolation algorithm, and analysis the process of interpolation function's derived and access. Give out the correction algorithm based on RBF neural network. With full study of The RBF neural network, give out the implementing the specific application correction algorithm with neural network. Several corrections algorithm of remote sensing images firstly get ground control points in the original image, and then select the point according with the need, then use them to make the interpolation function or the neural networks, and finally correct the remote sensing image with the interpolation function or neural network.The algorithm is simple, accurate and easy to implement, is a more practical remote sensing image correction algorithm.