Bachelor Thesis: Automatic correction of shift and rotation of images from different sources for machine learning application

Intern / Student, Part-time ยท Munich

Your tasks
Aerial images from drones, planes or satellites represent the captures surface with a geo reference. Due to influencing factors (optics of the systems used, precision of geo location during capture, algorithms used for ortho processing, etc.), images from different soures are not totally aligned. Usually, ther's a shift and rotation visible when overlaying images. Both shift and rotation might have a non-linear spread across all imagery. This is an impediment for the joint use of images from different sources, especially if high accuracy geo referencing is required.

Objective is to develop an automated procedure to determine the required (elastic) transformation between different images based on given reference points. Special attention needs to be paid to keep quality and machine learning relevant attributes unaltered during the transformation process.
Requirements
Skillsets:
  • Programming with Python
  • Coordinate transformations, map projections
  • use of image libraries like GDAL etc.
  • Visualization with GIS tools
Areas of expertise:
  • Coordinate systems
  • GIS
  • Statistics
Life as TerraLouper is
  • exciting to be part of a highly motivated, international top team of engineers
  • interesting to work with cutting-edge technologies, agile development practices and product-focused environment
  • office location in the heart of Munich
  • flexible working hours
  • multi-cultural team
About us
TerraLoupe is a German startup to empower autonomous mobility. We use machine learning technology to automaticcally detect objects from aerial imagery to create a 3D digital twin of the world. Located in the heart of Munich the next level of geo platform and HD mapping is getting to reality.
Your application
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