Deep learning-based marker detection for autonomous drone landing is widely studied, due to its superior detection performance. However, no study was reported to address non-uniform motion-blurred input images, and most of the previous handcrafted an...
We propose a video deblurring method by combining motion compensation with spatiotemporal constraint for restoring blurry video caused by camera shake. The proposed method makes effective full use of the spatiotemporal information not only in the blu...
Unmanned aerial vehicles (UAVs) have been increasingly utilized for facility safety inspections due to their superior safety, cost effectiveness, and inspection accuracy compared to traditional manpower-based methods. High-resolution images captured...
The single-pixel imaging technique is applied to spatial frequency domain imaging (SFDI) to bring significant performance advantages in band extension and sensitivity enhancement. However, the large number of samplings required can cause severe quali...
Motion image deblurring remains challenging because many existing models rely on complex architectures, leading to high computational cost and parameter redundancy, particularly under non-uniform blur in real-world scenes. To mitigate these limitatio...
Motion deblurring is an essential capability for high-speed vision applications such as autonomous driving and unmanned aerial vehicles. Existing frame-based deblurring methods often struggle with rapid motion, whereas event cameras offer a promising...
Despite the significant number of classification studies conducted using plant images, studies on nonlinear motion blur are limited. In general, motion blur results from movements of the hands of a person holding a camera for capturing plant images,...
In this paper, we present the multi-stage attentive network (MSAN), an efficient and good generalization performance convolutional neural network (CNN) architecture for motion deblurring. We build a multi-stage encoder–decoder network with self...
In general dynamic scenes, blurring is the result of the motion of multiple objects, camera shaking or scene depth variations. As an inverse process, deblurring extracts a sharp video sequence from the information contained in one single blurry image...
Underwater images often suffer from mixed degradations, including motion blur, which reduce structural clarity and adversely affect downstream vision tasks. To address this problem, we propose a physically guided Transformer framework for underwater...
This paper presents a novel method of restoring the electron beam (EB) measurements that are degraded by linear motion blur. This is based on a fuzzy inference system (FIS) and Wiener inverse filter, together providing autonomy, reliability, flexibil...
Motion deblurring is an ill-posed, challenging problem in image restoration due to non-uniform motion blurs. Although recent deep convolutional neural networks have made significant progress, many existing methods adopt multi-scale or multi-patch sub...
Unlike natural image deblurring, which primarily emphasizes perceptual quality and pixel-level fidelity, Quick Response (QR) code deblurring must retain decoding-critical structures to guarantee successful decoding. QR codes contain regular binary mo...
Among many available biometrics identification methods, finger-vein recognition has an advantage that is difficult to counterfeit, as finger veins are located under the skin, and high user convenience as a non-invasive image capturing device is used...
Motion blur weakens multi-view geometric consistency, causing 3D Gaussian Splatting (3DGS) to produce inaccurate geometry, floating artifacts, and blurred structures due to missing high-frequency information. Event cameras provide microsecond-level t...
Resolution decrease and motion blur are two typical image degradation processes that are usually addressed by deep networks, specifically convolutional neural networks (CNNs). However, since real images are usually obtained through multiple degradati...
Unmanned air vehicle (UAV) based imaging has been an attractive technology to be used for wind turbine blades (WTBs) monitoring. In such applications, image motion blur is a challenging problem which means that motion deblurring is of great significa...
Detecting snow-covered solar panels is crucial as it allows us to remove snow using heating techniques more efficiently and restores the photovoltaic system to proper operation. This paper presents classification and detection performance analyses fo...
Motion blur is a complex phenomenon caused by the relative movement between an observed object and an imaging sensor during the exposure time, resulting in degradation in the image quality. Deep-learning-based methods, particularly convolutional neur...
In the dynamic visual cabinet, the occurrence of motion blur when consumers take out commodities will reduce the accuracy of commodity detection. Recently, although Transformer-based video deblurring networks have achieved results compared to Convolu...
Borescope inspection is a labour-intensive process used to find defects in aircraft engines that contain areas not visible during a general visual inspection. The outcome of the process largely depends on the judgment of the maintenance professionals...
Rolling shutter CMOS cameras are widely used in mobile and embedded vision, but rapid motion and vibration often cause coupled degradations, including motion blur and rolling shutter (RS) geometric distortion. This paper presents a visual–inert...
The motion of an object or camera platform makes the acquired image blurred. This degradation is a major reason to obtain a poor-quality image from an imaging sensor. Therefore, developing an efficient deep-learning-based image processing method to r...
Real-world motion blur exhibits complex, spatially varying characteristics that challenge existing deblurring methods. While multi-stage architectures offer progressive refinement, simple inter-stage interactions often limit effective information tra...
A periodic rotational-scanning panoramic imaging system (PRS imaging system) can acquire large-scale, continuous, and high-resolution panoramic images through rotational scanning. However, non-ideal camera motion during exposure introduces spatially...
Various types of motion blur are frequently observed in the images captured by sensors based on thermal and photon detectors. The difference in mechanisms between thermal and photon detectors directly results in different patterns of motion blur. Mot...
Bolted connections are essential components that require regular inspection to ensure bridge safety. Existing methods mainly rely on traditional artificial vision-based inspection, which is inefficient due to the many bolts of bridges. A vision-based...
Image restoration lies between camera acquisition and geometric estimation, but pixel improvements may not transfer to motion estimates. We evaluated directional-kernel Richardson–Lucy (RL) deblurring under kernel-length and direction controls....
Image reconstruction in nighttime dynamic scenes is challenged by low illumination, long exposure, rapid camera or object motion, and sensor noise. Conventional RGB cameras, therefore, struggle to recover both sufficient brightness and clear structur...
The combination of gesture recognition and aerospace exploration robots can realize the efficient non-contact control of the robots. In the harsh aerospace environment, the captured gesture images are usually blurred and damaged inevitably. The motio...
Recent studies have proposed methods for extracting latent sharp frames from a single blurred image. However, these methods still suffer from limitations in restoring satisfactory images. In addition, most existing methods are limited to decomposing...
Object tracking in thermal video is challenging due to noise, blur, and low contrast. We present TVEMamba, a Mamba-based enhancement framework with near-linear complexity that improves tracking in these conditions. Our approach uses a State Space 2D...
Various studies have been conducted to reduce the blurring caused by movement in cine magnetic resonance imaging (MRI) of the heart. This study proposed a blind deconvolution method using a total variation regularization algorithm to remove blurring...
The visualization of motion is important in the diagnosis and treatment of aortic valve disease. It is difficult to perform using computed tomography (CT) because of motion blur. Existing research focuses on suppressing or removing motion blur. The p...
Blind image restoration algorithms for motion blur have been deeply researched in the past years. Although great progress has been made, blurred images containing large blur and rich, small details still cannot be restored perfectly. To deal with the...
Video deblurring aims at removing the motion blur caused by the movement of objects or camera shake. Traditional video deblurring methods have mainly focused on frame-based deblurring, which takes only blurry frames as the input to produce sharp fram...
Edge detection serves as the foundation for advanced image processing tasks. The accuracy of edge detection is significantly reduced when applied to motion-blurred images. In this paper, we propose an effective deblurring method adapted to the edge d...
Drones have emerged as a critical tool for the detection of high-altitude glass curtain cracks. However, their utility is often compromised by vibrations and other environmental factors that can induce motion blur, compromising image quality and the...
Complex marine environment has an adverse effect on the object detection algorithm based on the vision sensor for the smart ship sailing at sea. In order to eliminate the motion blur in the images during the navigation of the smart ship and ensure sa...
In image sensing, measurements such as an object’s position or contour are typically obtained by analyzing digitized images. This method is widely used due to its simplicity. However, relative motion or inaccurate focus can cause motion and def...
Medical image acquisition devices are susceptible to producing blurry images due to respiratory and patient movement. Despite having a notable impact on such blind-motion deblurring, medical image deblurring is still underexposed. This study proposes...
Automatic imaging monitoring technology has been developed as a mature solution to address oil spill accidents. However, when airborne equipment is used to monitor the area of leakage, there is a chance of relative motion between the equipment and th...
Image deblurring can improve visual quality and mitigates motion blur for dynamic visual inspection. We propose a method to deblur saturated images for dynamic visual inspection by applying blur kernel estimation and deconvolution modeling. The blur...
In order to improve the detection accuracy of an algorithm in the complex environment of a coal mine, including low-illumination, motion-blur, occlusions, small-targets, and background-interference conditions; reduce the number of model parameters; i...
Unmanned aerial vehicles (UAVs) have become an important technology for acquiring high-resolution remote sensing images. Because most space optical imaging systems of UAVs work in environments affected by vibrations, the optical axis motion and image...
Vehicle license plate images are often low resolution and blurry because of the large distance and relative motion between the vision sensor and vehicle, making license plate identification arduous. The extensive use of expensive, high-quality vision...
Motion blur is a common problem in the field of surveillance scenarios, and it obstructs the acquisition of valuable information. Thanks to the success of deep learning, a sequence of CNN-based architecture has been designed for image deblurring and...
Building occupancy information is significant for a variety of reasons, from allocation of resources in smart buildings to responding during emergency situations. As most people spend more than 90% of their time indoors, a comfortable indoor environm...
Image blur is a major factor that degrades object detection in agricultural applications, particularly in orchards where crop occlusion, leaf movement, and camera shake frequently reduce image quality. This study proposed a lightweight generative adv...
We report on the post-capture, on-demand deblurring technique based on a Dynamic Vision Sensor (DVS). Motion blur causes photographic defects inherently in most use cases of mobile cameras. To compensate for motion blur in mobile photography, we use...
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