23 papers · ranked by Valyu relevance
Tianyang Xu, Zhenhua Feng, Xiao‐Jun Wu, Josef Kittler
—With efficient appearance learning models, Discriminative Correlation Filter (DCF) has been proven to be very successful in recent video object tracking benchmarks and competitions. However, the existing DCF paradigm suffers from two major issues, i.e., spatial boundary effect and temporal filter degradation. To…
Ruturaj G. Gavaskar, Kunal N. Chaudhury
—In the classical bilateral filter, a fixed Gaussian range kernel is used along with a spatial kernel for edge-preserving smoothing. We consider a generalization of this filter, the socalled adaptive bilateral filter, where the center and width of the Gaussian range kernel is allowed to change from pixel to pixel.…
Xiong Xiong, Ying Wang, Tianyuan Song, Jinguo Huang + 1 more
As a typical self-paced brain-computer interface (BCI) system, the motor imagery (MI) BCI has been widely applied in fields such as robot control, stroke rehabilitation, and assistance for patients with stroke or spinal cord injury. Many studies have focused on the traditional spatial filters obtained through the…
David Menrath, Joshua P. Woller, Alireza Gharabaghi
Combining electrical neurostimulation with electroencephalography (EEG) for adaptive neurostimulation remains challenging due to the presence of stimulation artifacts in the recorded signal. Interpretation of EEG activity concurrent with stimulation requires real-time filtering of this noisy signal. While traditional…
Thomas W. Mitchel, Benedict J. Brown, David Koller, Tim Weyrich + 2 more
'Szymon Rusinkiewicz' 'Michael Kazhdan'] Fast methods for convolution and correlation underlie a variety of applications in computer vision and graphics, including efficient filtering, analysis, and simulation. However, standard convolution and correlation are inherently limited to fixed filters: spatial adaptation is…
Filippos Kokkinos, Ioannis Marras, Matteo Maggioni, Greg Slabaugh + 1 more
'Stefanos Zafeiriou'] State-of-the-art methods for computer vision rely heavily on the translation equivariance and spatial sharing properties of convolutional layers without explicitly taking into consideration the input content. Modern techniques employ deep sophisticated architectures in order to circumvent this…
Bevan L. Cheeseman, Ulrik Günther, Mateusz Susik, Krzysztof Gonciarz + 1 more
Modern microscopy modalities create a data deluge with gigabytes of data generated each second, or terabytes per day. Storing and processing these data is a severe bottleneck. We argue that this is an artifact of the images being represented on pixels. To address the root of the problem, we here propose the Adaptive…
Mahta Mousavi, Eric Lybrand, Shuangquan Feng, Shuai Tang + 2 more
'Rayan Saab' 'Virginia R. de'] Abstract. The method of Common Spatial Patterns (CSP) is widely used for feature extraction of electroencephalography (EEG) data, such as in motor imagery braincomputer interface (BCI) systems. It is a data-driven method estimating a set of spatial filters so that the power of the…
Liangliang Zheng, Wei Xu, Gwanggil Jeon, Renato Machado
Since remote sensing images are one of the main sources for people to obtain required information, the quality of the image becomes particularly important. Nevertheless, noise often inevitably exists in the image, and the targets are usually blurred by the acquisition of the imaging system, resulting in the degradation…
Peng Geng, Shuaiqi Liu, Shanna Zhuang
Medical image fusion plays an important role in diagnosis and treatment of diseases such as image-guided radiotherapy and surgery. The modified local contrast information is proposed to fuse multimodal medical images. Firstly, the adaptive manifold filter is introduced into filtering source images as the low-frequency…
Matthias Treder, Guido Nolte
A beamformer enhances the signal from a voxel of interest by minimising interference from all other locations represented in the sensor covariance matrix. However, the presence of narrowband oscillations in EEG/MEG implies that the spatial structure of the covariance matrix, and hence also the optimal beamformer…
David Abramian, Martin Larsson, Anders Eklund, Iman Aganj + 2 more
Brain activation mapping using functional magnetic resonance imaging (fMRI) has been extensively studied in brain gray matter (GM), whereas in large disregarded for probing white matter (WM). This unbalanced treatment has been in part due to controversies in relation to the nature of the blood oxygenation…
Hejin Cheong, Eunjung Chae, Eunsung Lee, Gwanghyun Jo + 1 more
This paper presents a fast adaptive image restoration method for removing spatially varying out-of-focus blur of a general imaging sensor. After estimating the parameters of space-variant point-spread-function (PSF) using the derivative in each uniformly blurred region, the proposed method performs spatially adaptive…
Hai Lin, Jie Wang, Junxiang Ge, Shunjun Wei
A new method using three dimensions of cloud continuity, including range dimension, Doppler dimension, and time dimension, is proposed to discriminate cloud from noise and detect more weak cloud signals in vertically pointing millimeter-wave cloud radar observations by fully utilizing the spatiotemporal continuum of…
Marius Klug, Niels A. Kloosterman
Removing power line and other frequency-specific artifacts from electrophysiological data without affecting neural signals remains a challenging task. Recently, an approach was introduced that combines spectral and spatial filtering to effectively remove line noise: Zapline (2). This algorithm, however, requires manual…
Jakub Grabek, Bogusław Cyganek
Real signals are usually contaminated with various types of noise. This phenomenon has a negative impact on the operation of systems that rely on signals processing. In this paper, we propose a tensor-based method for speckle noise reduction in the side-scan sonar images. The method is based on the Tucker decomposition…
Marek Szczepański, Krystian Radlak
We propose a novel filtering technique capable of reducing the multiplicative noise in ultrasound images that is an extension of the denoising algorithms based on the concept of digital paths. In this approach, the filter weights are calculated taking into account the similarity between pixel intensities that belongs…
Zixi Guan, Raja Varma Pamba, Bhuvaneswari Balachander, Deepak Kumar Khare + 2 more
'Deepak Kumar Khare' 'Nabamita Deb' 'Rajasekhar Boddu'] This paper introduces the application and classification of an adaptive filtering algorithm in the image enhancement algorithm. And the filtering noise reduction impact is compared using MATLAB software for programming, image processing, LMS algorithm, RLS…
Georges Chabouh, Baptiste Pialot, Louise Denis, Raphael Dumas + 3 more
Ultrasound Localization Microscopy (ULM) has been applied in various preclinical settings and in the clinic to reveal the microvasculature in deep organs. However, most ULM images employ standard Delay-and-Sum (DAS) beamforming. In standard ULM conditions, lengthy acquisition times are required to fully reconstruct…
Alejandro Mestre-Quereda, Juan M. Lopez-Sanchez, Jordi J. Mallorqui, Hanwen Yu + 3 more
'Hanwen Yu' 'Mi Wang' 'Jianlai Chen' 'Ying Zhu'] A geometrical decorrelation constitutes one of the sources of noise present in Synthetic Aperture Radar (SAR) interferograms. It comes from the different incidence angles of the two images used to form the interferograms, which cause a spectral (frequency) shift between…
Authors not listed
Machine olfaction—the artificial replication of the sense of smell—faces significant challenges due to the absence of large, standardized training datasets. Unlike vision, language, and audio models, which benefit from extensive corpora such as ImageNet, GLUE, and AudioSet, olfaction lacks scaled equivalents and…
Authors not listed
Scanning emission-based microscopies, such as X-ray fluorescence (XRF) and energy-dispersive X-ray spectroscopy, offer nanometer-scale chemical maps, but suffer from long acquisition times and radiation damage. Lower-flux and shorter dwell time scans mitigate this problem, but the resulting signal loss can only…
Authors not listed
For applications in gas sensing, purification, and capture, we often wish to search a large set of metal-organic frameworks (MOFs) for the top-K in terms of their Henry coefficient of an adsorbate. A molecular simulation to predict the Henry coefficient of a MOF constitutes a Monte Carlo integration where each sample…