Master Thesis – Methods for Characterizing Optics and Image Reconstruction in LWIR Sensors

Master Thesis – Methods for Characterizing Optics and Image Reconstruction in LWIR Sensors

Job Description

Category 

Thermal Imaging, LWIR sensor, Microbolometer, Optics  

Scope 

Two Master students, 30hp each 

Background 

The focal plane array (FPA) of a thermal sensor consists of individual pixels which have different signal responsivities and offsets. Furthermore, individual signal responsivities and offsets drift with time and vary with ambient temperature. Both lead to fixed-pattern and column noise. To be able to obtain images of good quality, some form of correction and calibration must be carried out. The former can be corrected by placing a black body with homogeneous temperature in front of the sensor, forcing each pixel to have the same response. This procedure can be done at a single temperature, ensuring uniform responses close to the temperature; or at two temperatures, ensuring uniformity between two temperatures (assuming linear responsivity between the two temperature points). The latter indicates that the correction must be done periodically. This is usually done by having an auto-shutter process.

The aim of this master thesis project is to deepen our understanding of the signal response of microbolometers, build a model to predict pixel responsivity at various ambient temperatures including optical effects and thermal drift with time. This can be beneficial for future thermal camera development by, for example, simplifying calibration procedures, removing shutters, etc. 

Goals 

• Investigate the limitations of operating without a shutter 

• Improve understanding of fixed pattern noise correction 

• Explore the limits of sensor calibration without optics.   

• Build a prototype camera based on our conventional products to demonstrate the results 

Who are you?

Absolute requirements 

• Programming skills in one or more of the following: Python/C++/C 

Appreciated requirements 

• Coursework in computer vision/image analysis  

• An understanding within optical sciences

Who to contact for any questions regarding the position! 

• Supervisors: Leif Gellersen, [email protected] and Jimmy Heimdal, [email protected]  

• Manager: Daniel Larsson, [email protected]

Type of Employment

Thesis Worker (Fixed Term)

Posting End Date

2026-11-27

Certain roles at Axis require background checks, which means applicable verifications will be done in these recruitments. Notice will be provided before we take any action.

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