Image Denoising Method Based on Discrete Shearlet Transform and Optimized Deep Convolutional Neural Network
Marine test images are often affected by factors such as marine meteorological conditions,seawater light refraction,and ocean depth,resulting in severe noise in the images collected in the ocean.In order to improve the clarity and denoising performance of marine test images,this paper proposes a marine test image denoising method based on discrete shearlet transform combined with an optimized deep convolutional neural network.The discrete shearlet transform is used to decompose the marine test image,which can effectively extract features of different directions and frequencies from the image.By utilizing the powerful feature extraction ability of the optimized deep convolutional neural network,after training the network model,key features in the image can be obtained,thus achieving the purpose of denoising.In the verification experiment,compared with traditional image denoising methods,the proposed method can effectively retain the texture and detail characteristics of the image,achieve good denoising effect,and improve the clarity and denoising performance of marine test images.
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