Acceleration algorithm for constant-statistics method applied to the nonuniformity correction of infrared sequences

Chavez, Arturo Gomez; Vicencio, F.O. Torres

doi:10.1515/oere-2015-0014

Cited by 6 publications

(4 citation statements)

References 8 publications

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“…The second approach is scene-based correction, which updates FPA parameters iteratively utilizing information extracted from inter-frame motion of real scene images [16]. Statistical analysis [17,18], algebraic computation [19], Kalman filter [20], temporal high-pass filter [21,22], image registration [23], and neural networks [16,24] have all been utilized in scene-based correction algorithms, although most of them were intended for correcting strip noise rather than vignetting. While scene-based techniques remove the need for a shutter and show better correction performance for time-varying offset and variable integration time [25], they are computationally complex, typically require multiple image frames, and do not guarantee corrected temperature accuracy [11,26].…”

Section: Introductionmentioning

confidence: 99%

A Case Study of Vignetting Nonuniformity in UAV-Based Uncooled Thermal Cameras

Yuan¹,

Hua

2022

Drones

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Uncooled thermal cameras have been employed as common UAV payloads for aerial temperature surveillance in recent years. Due to the lack of internal cooling systems, such cameras often suffer from thermal-drift-induced nonuniformity or vignetting despite having built-in mechanisms to minimize the noise. The current study examined a UAV-based uncooled thermal camera vignetting regarding camera warmup time, ambient temperature, and wind speed and direction, and proposed a simple calibration-based vignetting migration method. The experiments suggested that the camera needed to undergo a warmup period to achieve stabilized performance. The required warmup duration ranged from 20 to 40 min depending on ambient temperature. Camera vignetting severity increased with camera warmup time, decreasing ambient temperature, and wind presence, while wind speed and direction did not make a difference to camera vignetting during the experiments. Utilizing a single image of a customized calibration target, we were able to mitigate vignetting of outdoor images captured in a 30 min duration by approximately 70% to 80% in terms of the intra-image pixel standard deviation (IISD) and 75% in terms of the pixel-wise mean (PWMN) range. The results indicated that outdoor environmental conditions such as air temperature and wind speed during short UAV flights might only minimally influence the thermal camera vignetting severity and pattern. Nonetheless, frequent external shutter-based corrections and considering the camera nonlinear temperature response in future studies have the potential to further improve vignetting correction efficacy for large scene temperature ranges.

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Section: Introductionmentioning

confidence: 99%

A Case Study of Vignetting Nonuniformity in UAV-Based Uncooled Thermal Cameras

Yuan¹,

Hua

2022

Drones

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“…Studying the rupture process of geotechnical materials has important theoretical significance and practical value for evaluating the safety state of geotechnical engineering, understanding the stability of geotechnical engineering structure, taking reasonable supporting measures, and improving the design level of geotechnical and underground structural engineering. The nonlinearity of macroscopic mechanical behavior of geotechnical materials in the process of fracture is due to the heterogeneity of their meso-structure [2][3][4]. Under the same experimental and loading conditions, the true microstructure and the mechanical properties of various meso-media play a decisive role in the stress and deformation responses of the specimens.…”

Section: Introductionmentioning

confidence: 99%

Research on establishing numerical model of geo material based on CT image analysis

Luo

Pan

Zhang

et al. 2019

J Image Video Proc.

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Geotechnical engineering material is a kind of heterogeneous composite material. The stone, mineral, gravel, hole, and crack contained in it have different physical and mechanical properties, and their responses to external forces are very different. For example, stress distribution, crack propagation, and failure mode are closely related to material heterogeneity and microstructure. This paper presents a finite element model method for processing CT images of geotechnical materials by using digital image technology. This paper presents a finite element model method for processing CT images of geotechnical materials by using digital image technology. The theory of digital image processing is applied to geotechnical CT image processing to realize pseudo-color enhancement of CT image, and the histograms of different geotechnical CT numbers are obtained. Canny operator is used to detect the edge of geotechnical CT image, and the binary image of geotechnical microstructure is obtained. According to the color change of pseudo-color enhanced image and CT histogram, the meso-structure and variation of rock and soil can be quantitatively analyzed. The finite element model established by this method can fully consider the heterogeneity of geotechnical materials, especially the effect of void distribution on the mechanical properties of geotechnical materials.

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“…Zuo et al [31] proposed an interframeregistration-based correction for NUC in IRFPAs, using a phase-correlation method to estimate the motion between two adjacent images and a least mean square algorithm to calculate the gain and offset correction coefficient of the FPA. Jara and Torres [32] presented a method to reduce FPN and ghosting artifacts using an enhanced constant statistics method that incorporates a motion threshold. Sheng-Hui et al [33] developed a neural network SBNUC method that combines a guided filter with an adaptive learning rate that demonstrated a decrease in observed ghosting artifacts.…”

Section: Introductionmentioning

confidence: 99%

A Unified Method for Digital Super-Resolution and Restoration in Infrared Microscopy Imaging

et al. 2019

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Infrared (IR) imaging systems are known to have a range of sensor and optical limitations that result in degraded imagery. Fixed pattern noise (FPN), resulting from pixel-to-pixel response nonuniformity, is a dominant source of error that manifests in collected imagery through the appearance of temporally and spatially correlated noise patterns that are mixed with each image. Furthermore, finite detector size coupled with imperfect system optics can introduce blurring effects and aliasing, ultimately reducing resolution in acquired images. Here, we propose a unified method to reduce FPN and recover high-frequency image content in IR microscopy images. The proposed method uses regularized nonlocal means to highlight spatial features in the scene while maintaining fine textural image details. We derive an iterative optimization method based upon a gradient descent minimization strategy that applies a Wiener deconvolution in each iteration to estimate the blur artifacts. The method is implemented within an embedded mid-wave IR imaging system for microscopy applications. We demonstrate a reduction in FPN and blurring artifacts, achieving improved image resolution in the reconstructed images that are apparent in recovered details on scene objects.

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Acceleration algorithm for constant-statistics method applied to the nonuniformity correction of infrared sequences

Cited by 6 publications

References 8 publications

A Case Study of Vignetting Nonuniformity in UAV-Based Uncooled Thermal Cameras

A Case Study of Vignetting Nonuniformity in UAV-Based Uncooled Thermal Cameras

Research on establishing numerical model of geo material based on CT image analysis

A Unified Method for Digital Super-Resolution and Restoration in Infrared Microscopy Imaging

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