Intelligent inspection UAV multispectral remote sensing images usually contain information from multiple frequency bands

thus having a high data dimension.A large amount of data needs to be processed during denoising and feature extraction

increasing the complexity of computation and processing.To this end

a method for enhancing multispectral remote sensing images of intelligent inspection UAV is studied.Firstly

the Contourlet transform is introduced to transform the denoising problem of low-quality inspection images into a Bayesian estimation problem

and inverse transformation estimation is performed on low-quality inspection images to complete the denoising of unmanned aerial vehicle multispectral remote sensing images.Combining wavelet transform with neural network

image is decomposed and reconstructed using wavelet transform

and neural network is used for image enhancement.The experimental results show that compared with traditional methods

the image enhancement effect of the research method is better.