Algorithm Development
We develop imaging and signal-processing algorithms that extract more information from every photon—enhancing reconstruction, denoising, detection, and measurement for SPAD, CMOS, and hybrid sensor systems. Our work is optimized for real-world constraints, from embedded compute to high-throughput pipelines.
About This Service?
Image Processing • Signal Processing • Photon Counting • Computational Imaging • Sensor-Aware Algorithms • Reconstruction
SWIRLabs builds advanced algorithms that turn raw sensor output into high-value, decision-ready data. We specialize in imaging and signal-processing methods designed specifically for photon-limited and high-dynamic-range environments—where conventional pipelines break down and physics-aware computation becomes essential.
Our algorithm work is tightly coupled to sensor architecture. We design sensor-aware approaches that account for real detector behavior (noise sources, timing jitter, dead time, crosstalk, nonuniformity, and readout constraints), allowing systems to achieve higher accuracy, better stability, and stronger performance under real-world conditions.
What We Build
Photon-Counting & Event-Based Processing
Algorithms for SPAD and event-driven sensors, including event aggregation, timestamp handling, pile-up mitigation, gating strategies, and rate correction—built to preserve timing fidelity and maximize usable signal.
Reconstruction & Computational Imaging
Model-based and learning-assisted reconstruction for low-light and sparse measurements, including inverse problems, deconvolution, super-resolution strategies, and physics-informed reconstruction workflows.
Image & Signal Processing Pipelines
Denoising, correction, enhancement, and feature extraction tuned for scientific, industrial, and defense imaging contexts—designed to improve reliability and interpretability, not just visuals.
Sensor-Aware Calibration & Correction
Nonuniformity correction, drift compensation, temperature-aware calibration, and artifact mitigation that incorporate known sensor behaviors and system-level constraints.
Detection, Tracking & Measurement
Algorithms that convert imagery into actionable outputs: detection and classification support, tracking, segmentation, and quantitative measurement—optimized for low SNR regimes.
How We Work
We start with the outcome you need (imaging quality, detection accuracy, measurement repeatability, throughput, latency) and design algorithms that respect the constraints of the full system:
- Photon budgets and shot-noise-dominated regimes
- Timing precision and synchronization requirements
- Readout bandwidth and compute limits
- Embedded vs GPU/CPU deployment realities
We deliver algorithms as production-ready components—validated against realistic sensor models and, when available, prototype data.
Deliverables
Depending on engagement scope, deliverables can include:
- Algorithm prototypes and reference implementations
- Performance benchmarking and tradeoff analyses
- Calibration/correction workflows and documentation
- Deployment-ready modules (embedded or high-throughput)
- Optional integration support with sensor/ROIC teams
Why SWIRLabs
We don’t treat algorithms as an afterthought. We build computation that is grounded in the physics of the sensor and the needs of the application—so performance gains hold up outside the lab.
