Abstract:

Aiming at the problem of random Gaussian noise in the process of remote sensing image acquisition caused by different lighting conditions， this paper studies the edge detection algorithm of noisy remote sensing image under different lighting conditions， so as to improve the accuracy of remote sensing image registration and recognition. Aiming at the random Gaussian noise in the process of remote sensing image acquisition under different illumination conditions， a windowed median filtering algorithm is constructed by combining the neighborhood mean filtering algorithm with the median filtering algorithm. The algorithm is used to filter the noisy remote sensing image to eliminate all kinds of noise conditions in the remote sensing image. For the denoised remote sensing image， the Canny operator is used to calculate the image gradient and constrain the maximum value. For the constrained gradient histogram of remote sensing image， the maximum interclass variance method is used to adaptively detect and connect the high and low thresholds of edges， and the edge detection of remote sensing image is completed by tracking edge pixels. The test results show that the algorithm can return the actual remote sensing image to the greatest extent， accurately detect the image edge information， and improve the accuracy of remote sensing image registration and recognition.

Key words: illumination conditions, noisy, remote sensing images, edge detection, filtering algorithm, maximum interclass variance