A Deep Learning-Based Depth Image Super-resolution Reconstruction Method
A super-resolution reconstruction and depth image technology, applied in the field of computer image processing, can solve the problems of general reconstruction effect, limited information utilization, low resolution, etc., and achieve the effect of accelerating training and convergence speed
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[0052] In order to solve the defects of the prior art, the present invention provides a deep learning-based depth map super-resolution reconstruction method, and the technical solution adopted in the present invention is:
[0053] 1. See figure 1 , which is a flow chart of the steps of the present invention. When the upsampling factor is 2, it includes the following steps:
[0054] (1) A certain number of depth images were selected from different public datasets of depth images, 102 images were selected, and the images with larger resolution in the public datasets were all selected.
[0055] (2) Data enhancement. In order to increase the training set samples, each image is rotated by 90°, 180°, and 270°, and then scaled by 0.8 and 0.9 times. After the enhancement, the number of images is increased to 12 times. At this time, a total of 1224 images are obtained. the final training set.
[0056] (3) Preprocess the obtained depth images in the training set. Because the image s...
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