# FPA-CS: Focal Plane Array-based Compressive Imaging in Short-wave Infrared

arXiv: https://arxiv.org/abs/1504.04085 · HTML: https://mlsanity.com/paper/1504.04085/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Apr 2015.

## Built on by (most cited first, 3 of 3)

- [AceVFI: A Comprehensive Survey of Advances in Video Frame Interpolation](https://mlsanity.com/paper/2506.01061/) (2025)
- [CalibFPA: A Focal Plane Array Imaging System based on Online Deep-Learning Calibration](https://mlsanity.com/paper/2309.11421/) (2023)
- [Does AI Understand Imaging? A Systematic Benchmark of Agentic AI for Computational Imaging Tasks](https://mlsanity.com/paper/2607.07189/) (2026)

## Abstract (arXiv)

Cameras for imaging in short and mid-wave infrared spectra are significantly more expensive than their counterparts in visible imaging. As a result, high-resolution imaging in those spectrum remains beyond the reach of most consumers. Over the last decade, compressive sensing (CS) has emerged as a potential means to realize inexpensive short-wave infrared cameras. One approach for doing this is the single-pixel camera (SPC) where a single detector acquires coded measurements of a high-resolution image. A computational reconstruction algorithm is then used to recover the image from these coded measurements. Unfortunately, the measurement rate of a SPC is insufficient to enable imaging at high spatial and temporal resolutions. We present a focal plane array-based compressive sensing (FPA-CS) architecture that achieves high spatial and temporal resolutions. The idea is to use an array of SPCs that sense in parallel to increase the measurement rate, and consequently, the achievable spatio-temporal resolution of the camera. We develop a proof-of-concept prototype in the short-wave infrared using a sensor with 64× 64 pixels; the prototype provides a 4096× increase in the measurement rate compared to the SPC and achieves a megapixel resolution at video rate using CS techniques.