Evidence map›Paper›PMID 37836931›Full record

ArticleSensors (Basel, Switzerland)2023

Multi-Scale FPGA-Based Infrared Image Enhancement by Using RGF and CLAHE.

Jialong Liu, Xichuan Zhou, Zhenlong Wan, Xuefei Yang, Wei He, Rulong He, Yingcheng Lin

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Jialong LiuThe School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China.ORCID 0009-0006-4812-7416
Xichuan ZhouThe School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China.
Zhenlong WanNational Information Center of GACC, Beijing 100010, China.
Xuefei YangThe School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China.
Wei HeThe School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China.
Rulong HeThe School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China.
Yingcheng LinThe School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China.ORCID 0000-0002-7478-3103

Funding

National Key Research and Development Program of China 2021YFC3340500
6 · The paper itself

Abstract

Infrared sensors capture thermal radiation emitted by objects. They can operate in all weather conditions and are thus employed in fields such as military surveillance, autonomous driving, and medical diagnostics. However, infrared imagery poses challenges such as low contrast and indistinct textures due to the long wavelength of infrared radiation and susceptibility to interference. In addition, complex enhancement algorithms make real-time processing challenging. To address these problems and improve visual quality, in this paper, we propose a multi-scale FPGA-based method for real-time enhancement of infrared images by using rolling guidance filter (RGF) and contrast-limited adaptive histogram equalization (CLAHE). Specifically, the original image is first decomposed into various scales of detail layers and a base layer using RGF. Secondly, we fuse detail layers of diverse scales, then enhance the detail information by using gain coefficients and employ CLAHE to improve the contrast of the base layer. Thirdly, we fuse the detail layers and base layer to obtain the image with global details of the input image. Finally, the proposed algorithm is implemented on an FPGA using advanced high-level synthesis tools. Comprehensive testing of our proposed method on the AXU15EG board demonstrates its effectiveness in significantly improving image contrast and enhancing detail information. At the same time, real-time enhancement at a speed of 147 FPS is achieved for infrared images with a resolution of 640 × 480.

Indexed as

FPGAinfrared image enhancementmulti-scale decompositionreal-time

Identifiers

PMID37836931
PMCPMC10575104

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.