Core CT image super-resolution reconstruction method based on three-dimensional convolutional neural network
A technology of super-resolution reconstruction and three-dimensional convolution, which is applied in the field of image repair enhancement and core three-dimensional image super-resolution. Effect
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[0049] In order to make the restoration method of the present invention easier to understand and closer to the real application, the following is an overall description of the entire process from the preprocessing of the original core CT training samples to the completion of the CT image super-resolution reconstruction, including the three-dimensional super-resolution of the present invention. Identify how to rebuild the network using:
[0050] (1) Using CT machine to scan the cut small core samples, multiple continuous two-dimensional image sequences can be obtained, which are sequentially read in and stored to generate three-dimensional images. The CT three-dimensional image as figure 1 shown. Extract 400 continuous pictures from it, cut out a 400*400 pixel area for each single two-dimensional picture, and select 10 groups from different types of rock samples according to such rules as the training set and test set. The training set images are as follows: image 3 , 4 , 5...
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