Depth image super-resolution reconstruction method based on deep learning

Abstract

The invention discloses a depth image super-resolution reconstruction method based on deep learning, and the method comprises the steps: training the whole network when an upsampling factor r is equalto 2, and comprises the steps: selecting a certain number of depth images from different depth image public data sets; and data enhancement: designing a deep convolutional neural network structure: training the whole network by using the processed network input data and the data label, inputting the low-resolution depth image into the trained network model after the training is completed, and outputting the depth image of which the super-resolution is completed on an output layer. According to the method, the high-dimensional feature map is generated through simultaneous training of multiplechannels of the convolutional neural network, the accurate pixel value of the original low-resolution image is reserved, and the training and convergence speed of the whole network is increased.

Description

technical field [0001] The invention belongs to the field of computer image processing, in particular to a depth image super-resolution reconstruction method based on deep learning. Background technique [0002] In recent years, due to the development of computer vision technology, the acquisition and processing of depth information has become one of the hot research directions. Different from the traditional two-dimensional color picture, the depth image contains the depth information of the scene, and intuitively reflects the geometric shape of the visible surface of the scene and the distance from the object to the camera through the pixel value. Therefore, depth images can be widely used in 3D reconstruction, human recognition, robot navigation, cultural relic protection, human-computer interaction and other fields. Currently, depth image super-resolution reconstruction methods are mainly divided into three categories: color image-guided depth image super-resolution rec...

AI Technical Summary

Problems solved by technology

The multi-depth image fusion super-resolution reconstruction method only uses the internal information of the depth image, and the input depth image has limited information due to its low resolution, and the reconstruction effect is general.

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