A Deep Learning-Based Depth Image Super-resolution Reconstruction Method

Abstract

The invention discloses a depth image super-resolution reconstruction method based on deep learning. When the upsampling factor r=2, training the entire network includes: selecting a certain number of depth images from different depth image public data sets; Enhancement: Design of deep convolutional neural network structure: The processed network input data and data labels are used to train the entire network. After the training is completed, the low-resolution depth image is input into the trained network model, and the output layer output is completed. resolution depth image. The invention generates a high-dimensional feature map through simultaneous training of multiple channels of a convolutional neural network, retains accurate pixel values ​​of the original low-resolution image, and accelerates the training and convergence speed of the entire network.

Description

technical field [0001] The invention belongs to the field of computer image processing, in particular to a deep learning-based deep image super-resolution reconstruction method. 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 image, the depth image contains the depth information of the scene, and directly reflects the geometric shape of the visible surface of the scene and the distance from the object to the camera through the size of the pixel value. Therefore, depth images can be widely used in 3D reconstruction, human body recognition, robot navigation, cultural relics protection, human-computer interaction and other fields. At present, depth image super-resolution reconstruction methods are mainly divided into three categories: color image-guided depth image super-reso...

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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