Image defogging and rain-removing algorithm based on selective attention mechanism
An attention and selective technology, applied in the field of image restoration, can solve the problem of insufficient restoration effect, and achieve the effect of accurate rain/fog removal
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[0053] The present invention proposes an image defogging and deraining algorithm based on a selective attention mechanism, including expanding training samples, training the network on the training set, defogging and deraining the test pictures, and combining the restored image with the clear image Three processes are assessed:
[0054] Expanding the training samples includes the following steps:
[0055] Step 1: The RESIDE indoor data set is used for the fog removal data set, and the Rain100H and Rain100L data sets are used for the rain removal data set. A part of the pictures in the training set in the data set are used as the verification set, and the remaining pictures in the training set are cropped, intercepted, rotated, etc. The original data set is expanded so that the image sizes in the defog and derain data sets are 640*460 and 100*100 respectively, which can avoid overfitting during training.
[0056] Training the network on the training set involves the following ...
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