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Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing

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Infrared image super resolution with structure prior from uncooled infrared readout circuit.

Kai Che¹, Jian Lv², Jia Wei¹

¹School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China.

Scientific Reports

|August 23, 2025

Summary

This study introduces an efficient infrared image super-resolution (SR) algorithm, EIRSR, inspired by readout circuits. It enhances resolution for uncooled infrared detector arrays, balancing performance and computational cost.

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Area of Science:

Computer Vision
Image Processing
Infrared Technology

Background:

Infrared images offer valuable temperature data but are limited by low resolution in uncooled detector arrays.
Existing infrared image super-resolution (SR) methods face challenges in efficiency and performance.
The need for high-resolution infrared imaging drives the development of advanced SR algorithms.

Purpose of the Study:

To develop an efficient infrared image super-resolution (SR) algorithm for uncooled infrared detector arrays.
To improve the reconstruction details and capture spatio-temporal correlations in infrared images.
To achieve a balance between performance and computational efficiency in infrared SR.

Main Methods:

Proposed an efficient Row-Column Transformer Block (RCTB) inspired by Uncooled Infrared Focal Plane Array (IRFPA) readout circuits.
Developed a Compact Convolution Block (CCB) with a U-shape Spatial Channel Attention Block (USCAB) for local feature extraction.
Incorporated a regularization control term in the loss function to enhance reconstruction details.
Introduced a hybrid network, Efficient Infrared Image Super-Resolution (EIRSR), and its variants (EIRSRs).

Main Results:

The proposed EIRSR network achieved a superior balance between performance and efficiency (parameters and computational cost).
EIRSR demonstrated competitive performance compared to existing state-of-the-art methods.
The model variants (EIRSRs) offer scalable solutions for infrared image super-resolution.

Conclusions:

The novel RCTB and CCB effectively capture spatio-temporal correlations and local features for infrared SR.
EIRSR provides an efficient and effective solution for enhancing the resolution of infrared images.
The proposed method contributes to advancing the capabilities of uncooled infrared imaging systems.