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A Low-Delay Dynamic Range Compression and Contrast Enhancement Algorithm Based on an Uncooled Infrared Sensor with Local Optimal Contrast

Real-time compression of images with a high dynamic range into those with a low dynamic range while preserving the maximum amount of detail is still a critical technology in infrared image processing. We propose a dynamic range compression and enhancement algorithm for infrared images with local opt...

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Autores principales: Zhu, Youpan, Zhou, Yongkang, Jin, Weiqi, Zhang, Li, Wu, Guanlin, Shao, Yiping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10649624/
https://www.ncbi.nlm.nih.gov/pubmed/37960559
http://dx.doi.org/10.3390/s23218860
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author Zhu, Youpan
Zhou, Yongkang
Jin, Weiqi
Zhang, Li
Wu, Guanlin
Shao, Yiping
author_facet Zhu, Youpan
Zhou, Yongkang
Jin, Weiqi
Zhang, Li
Wu, Guanlin
Shao, Yiping
author_sort Zhu, Youpan
collection PubMed
description Real-time compression of images with a high dynamic range into those with a low dynamic range while preserving the maximum amount of detail is still a critical technology in infrared image processing. We propose a dynamic range compression and enhancement algorithm for infrared images with local optimal contrast (DRCE-LOC). The algorithm has four steps. The first involves blocking the original image to determine the optimal stretching coefficient by using the information of the local block. In the second, the algorithm combines the original image with a low-pass filter to create the background and detailed layers, compressing the background layer with a dynamic range of adaptive gain, and enhancing the detailed layer for the visual characteristics of the human eye. Third, the original image was used as input, the compressed background layer was used as a brightness-guided image, and the local optimal stretching coefficient was used for dynamic range compression. Fourth, an 8-bit image was created (from typical 14-bit input) by merging the enhanced details and the compressed background. Implemented on FPGA, it used 2.2554 Mb of Block RAM, five dividers, and a root calculator with a total image delay of 0.018 s. The study analyzed mainstream algorithms in various scenarios (rich scenes, small targets, and indoor scenes), confirming the proposed algorithm’s superiority in real-time processing, resource utilization, preservation of the image’s details, and visual effects.
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spelling pubmed-106496242023-10-31 A Low-Delay Dynamic Range Compression and Contrast Enhancement Algorithm Based on an Uncooled Infrared Sensor with Local Optimal Contrast Zhu, Youpan Zhou, Yongkang Jin, Weiqi Zhang, Li Wu, Guanlin Shao, Yiping Sensors (Basel) Article Real-time compression of images with a high dynamic range into those with a low dynamic range while preserving the maximum amount of detail is still a critical technology in infrared image processing. We propose a dynamic range compression and enhancement algorithm for infrared images with local optimal contrast (DRCE-LOC). The algorithm has four steps. The first involves blocking the original image to determine the optimal stretching coefficient by using the information of the local block. In the second, the algorithm combines the original image with a low-pass filter to create the background and detailed layers, compressing the background layer with a dynamic range of adaptive gain, and enhancing the detailed layer for the visual characteristics of the human eye. Third, the original image was used as input, the compressed background layer was used as a brightness-guided image, and the local optimal stretching coefficient was used for dynamic range compression. Fourth, an 8-bit image was created (from typical 14-bit input) by merging the enhanced details and the compressed background. Implemented on FPGA, it used 2.2554 Mb of Block RAM, five dividers, and a root calculator with a total image delay of 0.018 s. The study analyzed mainstream algorithms in various scenarios (rich scenes, small targets, and indoor scenes), confirming the proposed algorithm’s superiority in real-time processing, resource utilization, preservation of the image’s details, and visual effects. MDPI 2023-10-31 /pmc/articles/PMC10649624/ /pubmed/37960559 http://dx.doi.org/10.3390/s23218860 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhu, Youpan
Zhou, Yongkang
Jin, Weiqi
Zhang, Li
Wu, Guanlin
Shao, Yiping
A Low-Delay Dynamic Range Compression and Contrast Enhancement Algorithm Based on an Uncooled Infrared Sensor with Local Optimal Contrast
title A Low-Delay Dynamic Range Compression and Contrast Enhancement Algorithm Based on an Uncooled Infrared Sensor with Local Optimal Contrast
title_full A Low-Delay Dynamic Range Compression and Contrast Enhancement Algorithm Based on an Uncooled Infrared Sensor with Local Optimal Contrast
title_fullStr A Low-Delay Dynamic Range Compression and Contrast Enhancement Algorithm Based on an Uncooled Infrared Sensor with Local Optimal Contrast
title_full_unstemmed A Low-Delay Dynamic Range Compression and Contrast Enhancement Algorithm Based on an Uncooled Infrared Sensor with Local Optimal Contrast
title_short A Low-Delay Dynamic Range Compression and Contrast Enhancement Algorithm Based on an Uncooled Infrared Sensor with Local Optimal Contrast
title_sort low-delay dynamic range compression and contrast enhancement algorithm based on an uncooled infrared sensor with local optimal contrast
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10649624/
https://www.ncbi.nlm.nih.gov/pubmed/37960559
http://dx.doi.org/10.3390/s23218860
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