Fixed-pattern noise model for filters in uncooled infrared focal plane array imaging optical paths

Pan, Yuan; Tan, Zhixin; Xu, Zijian; Wang, Minghe; Jin, Weiqi; Li, Li; Su, Binghua

doi:10.1016/j.infrared.2023.104790

Cited by 1 publication

(2 citation statements)

References 9 publications

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“…In the Histogram Clipping step, the frequency values of histogram bin values for each region are clipped using Equations ( 10)- (13).…”

Section: Histogram Clippingmentioning

confidence: 99%

“…Especially in the case of research and development (R&D) centers within the automotive industry, LWIR-based cameras are being developed for use as night vision systems among various infrared wavelengths, as they must produce finished products that meet standards such as ISO-26262. LWIR-based thermal-imaging cameras typically employ two detectors, categorized as either (1) cooled or (2) uncooled [11][12][13]. Cooled detectors provide high-quality image acquisition but are expensive to produce, large in size, and require significant power, so they are mainly used in applications such as defense.…”

Section: Introductionmentioning

confidence: 99%

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Contrast Enhancement Method Using Region-Based Dynamic Clipping Technique for LWIR-Based Thermal Camera of Night Vision Systems

Choi,

Han,

Cha

et al. 2024

Sensors

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In the autonomous driving industry, there is a growing trend to employ long-wave infrared (LWIR)-based uncooled thermal-imaging cameras, capable of robustly collecting data even in extreme environments. Consequently, both industry and academia are actively researching contrast-enhancement techniques to improve the quality of LWIR-based thermal-imaging cameras. However, most research results only showcase experimental outcomes using mass-produced products that already incorporate contrast-enhancement techniques. Put differently, there is a lack of experimental data on contrast enhancement post-non-uniformity (NUC) and temperature compensation (TC) processes, which generate the images seen in the final products. To bridge this gap, we propose a histogram equalization (HE)-based contrast enhancement method that incorporates a region-based clipping technique. Furthermore, we present experimental results on the images obtained after applying NUC and TC processes. We simultaneously conducted visual and qualitative performance evaluations on images acquired after NUC and TC processes. In the visual evaluation, it was confirmed that the proposed method improves image clarity and contrast ratio compared to conventional HE-based methods, even in challenging driving scenarios such as tunnels. In the qualitative evaluation, the proposed method demonstrated upper-middle-class rankings in both image quality and processing speed metrics. Therefore, our proposed method proves to be effective for the essential contrast enhancement process in LWIR-based uncooled thermal-imaging cameras intended for autonomous driving platforms.

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“…In the Histogram Clipping step, the frequency values of histogram bin values for each region are clipped using Equations ( 10)- (13).…”

Section: Histogram Clippingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Contrast Enhancement Method Using Region-Based Dynamic Clipping Technique for LWIR-Based Thermal Camera of Night Vision Systems

Choi,

Han,

Cha

et al. 2024

Sensors

View full text Add to dashboard Cite

show abstract

Fixed-pattern noise model for filters in uncooled infrared focal plane array imaging optical paths

Cited by 1 publication

References 9 publications

Contrast Enhancement Method Using Region-Based Dynamic Clipping Technique for LWIR-Based Thermal Camera of Night Vision Systems

Contrast Enhancement Method Using Region-Based Dynamic Clipping Technique for LWIR-Based Thermal Camera of Night Vision Systems

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