phase-to-height images

This dataset includes various gauge blocks of different heights at different positions. This includes two sets of data with no targets and different measurement heights. Each data consists of 16 phase-shifting images and their corresponding Gray code images. The processing flow is as follows: first, obtain the unwrapped phases of each group data sequentially through the above images, and then using GRNN neural network to obtain phase offsets at different positions, and substituting them into all unwrapped phases, finally performing phase-to-height mapping on the unwrapped phases that eliminate phase offsets.All data is classified and stored in folders, good luck!

本数据集包含不同高度、不同位置的多种量规块。其中包含两组无目标数据，测量高度各异。每份数据包括16张相位移位图像及其对应的格雷码图像。数据处理流程如下：首先，通过上述图像依次获取每组数据的未展开相位，随后利用GRNN神经网络获取不同位置的相位偏移，并将这些偏移量代入所有未展开的相位中，最终对消除相位偏移后的未展开相位进行相位至高度的映射。所有数据均已分类并存储于文件夹中，祝您好运！

搜集汇总

背景与挑战

背景概述

该数据集包含不同高度和位置的量块数据，每组数据由16个相移图像和对应的格雷码图像组成，用于通过GRNN神经网络进行相位到高度的映射处理。数据集分类存储在文件夹中，适用于传感器相关研究。