A novel method for sensitivity modelling of optical gas imaging thermal cameras with warm filters

Olbrycht, R.

doi:10.1080/17686733.2021.1962096

Cited by 9 publications

(4 citation statements)

References 19 publications

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“…Although narrowband filters can provide thermal images with higher thermal contrast when compared with detectors without such spectral selection technology, they also restrict the radiation that actually reaches the detector, thereby reducing the thermal imager’s sensitivity, reducing its SNR, and increasing the thermal imager’s noise equivalent temperature difference (NETD) [ 51 ].…”

Section: Methodsmentioning

confidence: 99%

Gas Imaging with Uncooled Thermal Imager

Zhang,

Chen,

Lin

et al. 2024

Sensors

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Gas imaging has become one of the research hotspots in the field of gas detection due to its significant advantages, such as high efficiency, large range, and dynamic visualization. It is widely used in industries such as natural gas transportation, chemical, and electric power industries. With the development of infrared detector technology, uncooled thermal imagers are undergoing a developmental stage of technological advancement and widespread application. This article introduces a gas imaging principle and radiation transfer model, focusing on passive imaging technology and active imaging technology. Combined with the actual analysis, the application scenarios using uncooled thermal imaging cameras for gas imaging measurement are analyzed. Finally, the limitations and challenges of the development of gas imaging technology are analyzed.

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Section: Methodsmentioning

confidence: 99%

Gas Imaging with Uncooled Thermal Imager

Zhang,

Chen,

Lin

et al. 2024

Sensors

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“…Cooled and uncooled IR systems have become more and more popular mainly in industrial environments [38]. Such systems equipped with matrix sensors have been already applied for optical gas imaging (OGI) [40]. In order to achieve this goal, the comparative simulations using well-known ℓ1 and the proposed CNN-based decompression algorithms were carried out for different compression rates (CR).…”

Section: Examples Of ℓ1 Reconstructionmentioning

confidence: 99%

Application of a deep-learning neural network for image reconstruction from a single-pixel infrared camera

Urbaś,

Więcek

2024

Opto-Electronics Review

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The article presents the simulation results of a single-pixel infrared camera image reconstruction obtained by using a convolutional neural network (CNN). Simulations were carried out for infrared images with a resolution of 80 × 80 pixels, generated by a low-cost, low-resolution thermal imaging camera. The study compares the reconstruction results using the CNN and the ℓ1 reconstruction algorithm. The results obtained using the neural network confirm a better quality of the reconstructed images with the same compression rate expressed by the peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM).

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“…Using IRT to evaluate artworks is often perceived as more advantageous than using traditional inspection methods, owing to its non-destructive and inexpensive nature, as well as good ability to identify potential defects [14,15]. In contrast to IRT [16][17][18][19], ultrasonic testing, which is another commonly used inspection method, requires a couplant (usually liquid) material added between the probe and the surface to be inspected. However, it is not advised to use such technique for precious/brittle test subjects, because liquid couplings can cause damages to the artwork.…”

Section: Introductionmentioning

confidence: 99%

Simulation-aided infrared thermography with decomposition-based noise reduction for detecting defects in ancient polyptychs

Jiang,

Wang,

et al. 2023

Herit Sci

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In recent years, the conservation and protection of ancient cultural heritage have received increasing attention, and non-destructive testing (NDT), which can minimize the damage done to the test subject, plays an integral role therein. For instance, NDT through active infrared thermal imaging can be applied to ancient polyptychs, which can realize accurate detection of damage and defects existing on the surface and interior of the polyptychs. In this study, infrared thermography is used for non-invasive investigation and evaluation of two polyptych samples with different pigments and artificial defects, but both reproduced based on a painting by Pietro Lorenzetti (1280/85–1348) using the typical tempera technique of the century. It is noted that, to avoid as far as possible secondary damages done to the ancient cultural heritages, repeated damage-detection experiments are rarely carried out on the test subjects. To that end, numerical simulation is used to reveal the heat transfer properties and temperature distributions, as to perform procedural verification and reduce the number of experiments that need to be conducted on actual samples. Technique-wise, to improve the observability of the experimental results, a total variation regularized low-rank tensor decomposition algorithm is implemented to reduce the background noise and improve the contrast of the images. Furthermore, the efficacy of image processing is quantified through the structural-similarity evaluation.

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A novel method for sensitivity modelling of optical gas imaging thermal cameras with warm filters

Cited by 9 publications

References 19 publications

Gas Imaging with Uncooled Thermal Imager

Gas Imaging with Uncooled Thermal Imager

Application of a deep-learning neural network for image reconstruction from a single-pixel infrared camera

Simulation-aided infrared thermography with decomposition-based noise reduction for detecting defects in ancient polyptychs

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