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In many practical applications of long-range imaging such as biometrics and surveillance, thermal imagining modalities are often used to capture images in low-light and nighttime conditions. However, such imaging systems often suffer from…

计算机视觉与模式识别 · 计算机科学 2022-04-08 Kangfu Mei , Yiqun Mei , Vishal M. Patel

Atmospheric turbulence, a common phenomenon in daily life, is primarily caused by the uneven heating of the Earth's surface. This phenomenon results in distorted and blurred acquired images or videos and can significantly impact downstream…

计算机视觉与模式识别 · 计算机科学 2024-02-13 Xijun Wang , Santiago López-Tapia , Aggelos K. Katsaggelos

Atmospheric turbulence poses a significant challenge to the performance of object detection models. Turbulence causes distortions, blurring, and noise in images by bending and scattering light rays due to variations in the refractive index…

计算机视觉与模式识别 · 计算机科学 2024-05-13 Engin Uzun , Erdem Akagunduz

Atmospheric turbulence deteriorates the quality of images captured by long-range imaging systems by introducing blur and geometric distortions to the captured scene. This leads to a drastic drop in performance when computer vision…

计算机视觉与模式识别 · 计算机科学 2022-04-20 Nithin Gopalakrishnan Nair , Kangfu Mei , Vishal M. Patel

Correlated imaging through atmospheric turbulence is studied, and the analytical expressions describing turbulence effects on image resolution are derived. Compared with direct imaging, correlated imaging can reduce the influence of…

光学 · 物理学 2015-05-19 Pengli Zhang , Wenlin Gong , Xia Shen , Shensheng Han

Atmospheric turbulence in long-range imaging significantly degrades the quality and fidelity of captured scenes due to random variations in both spatial and temporal dimensions. These distortions present a formidable challenge across…

计算机视觉与模式识别 · 计算机科学 2024-10-02 Zhicheng Zou , Nantheera Anantrasirichai

Atmospheric turbulence has a degrading effect on the image quality of long-range observation systems. As a result of various elements such as temperature, wind velocity, humidity, etc., turbulence is characterized by random fluctuations in…

计算机视觉与模式识别 · 计算机科学 2022-04-20 Engin Uzun , Ahmet Anil Dursun , Erdem Akagunduz

Atmospheric turbulence poses a challenge for the interpretation and visual perception of visual imagery due to its distortion effects. Model-based approaches have been used to address this, but such methods often suffer from artefacts…

计算机视觉与模式识别 · 计算机科学 2024-03-01 P. Hill , N. Anantrasirichai , A. Achim , D. R. Bull

Purely RGB-based vision models often fail to provide reliable cues in challenging scenarios such as nighttime and fog, leading to degraded performance and safety risks. Infrared imaging captures heat-emitting sources and provides critical…

计算机视觉与模式识别 · 计算机科学 2026-05-08 Yuchen Guo , Junli Gong , Wenjun Dong , Yiuming Cheung , Weifeng Su

The present research proposes a new memory-efficient method using diffusion models to inject turbulent inflow conditions into Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS) for various flow problems. A guided diffusion…

This work combines the principles of the heat spreader method and imaging capability of the thermoreflectance measurements to measure the in-plane thermal conductivity of thin-films without the requirement of film suspension or multiple…

应用物理 · 物理学 2020-11-24 T. Zhu , D. H. Olson , P. E. Hopkins , M. Zebarjadi

Image restoration algorithms for atmospheric turbulence are known to be much more challenging to design than traditional ones such as blur or noise because the distortion caused by the turbulence is an entanglement of spatially varying…

图像与视频处理 · 电气工程与系统科学 2022-07-26 Zhiyuan Mao , Ajay Jaiswal , Zhangyang Wang , Stanley H. Chan

Time-resolved image sensors that capture light at pico-to-nanosecond timescales were once limited to niche applications but are now rapidly becoming mainstream in consumer devices. We propose low-cost and low-power imaging modalities that…

计算机视觉与模式识别 · 计算机科学 2022-11-10 Sacha Jungerman , Atul Ingle , Yin Li , Mohit Gupta

Atmospheric turbulence severely degrades video quality by introducing distortions such as geometric warping, blur, and temporal flickering, posing significant challenges to both visual clarity and temporal consistency. Current…

计算机视觉与模式识别 · 计算机科学 2026-05-21 Zhiming Liu , Zhicheng Zou , Nantheera Anantrasirichai

We describe a method for recovering the irradiance underlying a collection of images corrupted by atmospheric turbulence. Since supervised data is often technically impossible to obtain, assumptions and biases have to be imposed to solve…

计算机视觉与模式识别 · 计算机科学 2024-06-25 Dong Lao , Congli Wang , Alex Wong , Stefano Soatto

Restoring images distorted by atmospheric turbulence is a ubiquitous problem in long-range imaging applications. While existing deep-learning-based methods have demonstrated promising results in specific testing conditions, they suffer from…

图像与视频处理 · 电气工程与系统科学 2023-12-12 Xingguang Zhang , Zhiyuan Mao , Nicholas Chimitt , Stanley H. Chan

Ground based long-range passive imaging systems often suffer from degraded image quality due to a turbulent atmosphere. While methods exist for removing such turbulent distortions, many are limited to static sequences which cannot be…

图像与视频处理 · 电气工程与系统科学 2020-09-02 Zhiyuan Mao , Nicholas Chimitt , Stanley Chan

Optical images of transparent three-dimensional objects can be different from a replica of the object's cross section in the image plane due to refraction at the surface or in the body of the object. Simulations of the object's image are…

Atmospheric turbulence distorts visual imagery and is always problematic for information interpretation by both human and machine. Most well-developed approaches to remove atmospheric turbulence distortion are model-based. However, these…

计算机视觉与模式识别 · 计算机科学 2022-05-10 Nantheera Anantrasirichai

Direct estimation of Lagrangian turbulence statistics is essential for the proper modeling of dispersion and transport in highly obstructed canopy flows. However, Lagrangian flow measurements demand very high rates of data acquisition,…

流体动力学 · 物理学 2019-05-16 Ron Shnapp , Erez Shapira , David Peri , Yardena Bohbot-Raviv , Eyal Fattal , Alex Liberzon
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