Optimizing IR Camera Performance: The Role of Optical Simulation

Dhanush Samarla
Manohharr Pittala
04:00 MINS
September 12, 2025

Optical simulation is transforming IR camera design by enabling precise analysis and control of stray light for superior imaging performance. When we talk about light pollution, most people imagine glowing cityscapes that obscure the stars. In infrared (IR) imaging and sensing, however, the term takes on a different meaning: stray light. This refers to unwanted energy—reflections, scattering, or ghosting—that enters IR camera sensors. The consequences can be subtle but critical: reduced signal-to-noise ratio, blurred thermal patterns, or distorted imagery that compromise both system performance and reliability.

For industries that depend on IR imaging—whether in security, aerospace, automotive, or industrial monitoring—stray light represents a common yet serious challenge. As IR technologies continue to expand into areas like predictive maintenance, surveillance, and autonomous systems, the demand for clearer, more accurate data has never been higher. Any degradation caused by stray light directly impacts efficiency, safety, and decision-making.

Fig. 1 Night vision camera near a window resulting in the IR lights reflecting off the glass (Source: https://www.howtogeek.com)

What is Stray Light—and Why Does it Matter?

Stray light refers to any infrared radiation that reaches a camera’s sensor through unintended paths, usually via internal reflections, scattering from lens surfaces, or ghost images formed by imperfect optical design. The consequences can be severe: reduced signal-to-noise ratio (SNR), blurred thermal signatures, and distorted imagery that affects both qualitative insight and quantitative measurements. For applications in surveillance, predictive maintenance, or autonomous vehicles, even modest stray light can mean missed anomalies, inaccurate detection, and compromised operational safety.

Stray light is especially difficult to suppress in sophisticated IR systems where demands for compactness, broad wavelength coverage, and speed are pushing optical designs to their limits. A recent study noted that performance degradation due to internal optical issues—rather than just atmospheric effects—is now a top concern for system integrators.

The Traditional Approach: Costly and Slow

Historically, mitigating stray light meant building physical prototypes and conducting exhaustive lab tests. Engineers and designers tried broad sets of lens shapes, coatings, and baffles, hoping experimental iteration would reveal workable solutions. But this physical trial-and-error cycle involves considerable cost, time, and effort. For high-volume products or mission-critical devices, the inefficiencies are stark.

Enter Optical Simulation: Digital Twins for IR Cameras

Optical simulation tools such as Ansys Speos, CODE V, and ImSym now make it possible to analyze and optimize IR camera performance virtually, long before the first hardware is built. These platforms allow the creation of digital twins—fully detailed models that ‘see’ like the final product would. Through simulation, engineers can:

Fig. 2 Ray Tracing to detect critical ray paths in the Optical system (Source: https://www.ansys.com/blog/exploring-facets-of-stray-light-simulation)

Quantitative and Comparative Analysis

State-of-the-art simulation platforms also provide advanced analytics. For example, entropy-weighted evaluation techniques or the use of NIQE (Natural Image Quality Evaluator) allow quantitative measurement of improvement after each design iteration. These methods have shown that entropy-weighted optimization can enhance local signal-to-noise ratios by nearly 1.5×, providing direct validation for optical improvements.

Fig. 3 3-D Irradiance sensor on a Camera Baffle to detect light energy accumulation (https://www.ansys.com)

Virtual Sensors and Countermeasure Testing

By embedding virtual irradiance and luminance sensors within the simulation, designers measure where stray energy accumulates, how it shifts image quality, and which countermeasures work best. This means coatings, filters, or mechanical changes can be tested digitally—comparing dozens of alternative designs for efficiency and performance before committing resources to physical builds. Such simulation-driven workflows speed up the selection of optimal hardware and reduce costly cycles of hardware revision.

Industry Impact: Speed, Savings, and Clarity

As IR imaging moves into wider fields such as predictive maintenance, smart transportation, and autonomous operation, the ability to rapidly deliver high-performance systems is vital. Optical simulation reduces the cost of IR camera development, accelerates innovation, and ensures that the delivered product meets both regulatory and mission standards for clarity, accuracy, and reliability.

Conclusion

Optical simulation has fundamentally altered how IR cameras are designed for today’s high-stakes environments. By replacing physical trial-and-error with virtual prototyping and quantitative validation, tools such as Ansys Speos empower engineers to optimize designs, suppress stray light, and maximize camera performance with speed and precision. For organizations seeking the clearest, most reliable IR data across industrial, aerospace, or automotive sectors, simulation-led camera design is not just an advantage—it is the new standard.