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Monocular Depth Estimation to Predict Surface Reliefs of Mars

A different application of monocular depth estimation models

Mattia Gatti
TDS Archive
5 min readSep 4, 2023

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Photo by NASA on Unsplash

Several approaches to estimating surface elevation from a single image have been discussed in the literature. In a previous article, I discussed how it is possible to predict the depth of a single 2D image using a monocular estimation model. However, when the input to the model is an image of a particular surface, the prediction represents a Digital Elevation Model (DEM). In my first research paper I showed how a DEM of the surface of Mars can be obtained from 2D greyscale images using deep learning approaches. To better understand the idea I’m going to propose, I suggest you first to try the demo of the project here.

Introduction

As discussed in more detail in another story, the DEM of a surface is a grid of elevation values where each cell stores the elevation of a particular point on the surface:

Graphic visualization of a DEM. NSIDC, CC BY 2.0, via Wikimedia Commons

DEMs are usually represented graphically using color maps. In the image above, the highest points are red and the lowest points are purple.

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TDS Archive
TDS Archive

Published in TDS Archive

An archive of data science, data analytics, data engineering, machine learning, and artificial intelligence writing from the former Towards Data Science Medium publication.

Mattia Gatti
Mattia Gatti

Written by Mattia Gatti

Currently doing research into AI Remote Sensing. Writing about Deep Learning and Geospatial Data Analysis.

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