Remote sensing image cloud detection method based on UNET neural network

Abstract

The invention discloses a remote sensing image cloud detection method based on a UNET neural network. The method comprises the following steps of creating a cloud detection network with five lower sampling layers and five upper sampling layers, connecting the front four lower sampling layers of the cloud detection network with a convolution layer and a pooling layer in sequence, and connecting therear four upper sampling layers with a deconvolution layer in sequence; carrying out cloud labeling, manual rechecking and data enhancement processing on the original remote sensing image set, and dividing the processed remote sensing image set into a training set, an evaluation set and a test set; continuously optimizing the cloud detection network by using the training set and the test set; andperforming cloud detection on the remote sensing image by using the cloud detection network, and outputting a result picture of the cloud detection. The problem that the detection result is not idealdue to insufficient cloud feature extraction is solved, the detection precision is improved, and the universality of the algorithm is enhanced.

Description

technical field [0001] The invention relates to the field of remote sensing image detection, and more specifically, relates to a remote sensing image cloud detection method based on a UNET neural network. Background technique [0002] With the rapid development of satellite remote sensing technology, remote sensing images have been widely used in the fields of environment, agriculture, and meteorology. However, satellite remote sensing images of optical imaging are often easily affected by the weather, resulting in cloud occlusion in the image, which affects the further application and analysis of the image; images can only be taken when the weather conditions permit and there is no cloud at all, which not only affects timeliness, but also increases cost of operating the satellite. [0003] In the prior art, the processing of remote sensing images needs to extract various parameters from the pictures, or transform and map the pictures, and then perform threshold judgment. T...

AI Technical Summary

Problems solved by technology

[0004] In view of this, the main purpose of the present invention is to provide a remote sensing image cloud detection method based on the UNET neural network, which solves the problem of unsatisfactory detection results due to insufficient cloud feature extraction, improves detection accuracy, and strengthens the algorithm. universality

Images