Improved M-Net-based RGB color remote sensing image cloud detection method and system
A remote sensing image and cloud detection technology, applied in the field of deep learning and image recognition, can solve the problems of poor versatility and low accuracy of cloud detection, and achieve easy training, promotion of forward propagation and back propagation, good generalization and The effect of robustness
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[0038] Example 1
[0039] The present invention provides a RGB color remote sensing image cloud detection method based on improved M-Net, including:
[0040] Training stage: Step 1. Preprocess the image;
[0041] Since the training data set is small and the size is too large, taking into account the limitations of GPU memory, calculation speed and ensuring the timeliness of the segmentation method, the present invention enhances the training data set, mainly through flipping, saturation adjustment, Operations such as brightness adjustment, color adjustment and noise addition;
[0042] Taking into account the computer's video memory and calculation speed, the picture is cropped to 256×256 pixels. Calculate the average value of each image to be detected in the training set in the three dimensions of RGB, and subtract the average value, which can improve the speed and accuracy of training;
[0043] The label production process uses 2, 1 and 0 to indicate whether each pixel is "cloud", "c...
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