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Spatial filter

About: Spatial filter is a research topic. Over the lifetime, 6170 publications have been published within this topic receiving 100451 citations.


Papers
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Journal ArticleDOI
TL;DR: This work constructed a complete quantum circuit that implements the median filtering task and presented the results of several simulation experiments on some grayscale images with different noise patterns, showing that the proposed scheme can reduce the computational complexity of the classical median filter from the exponential function of image size n to the second-order polynomial function ofimage size n.
Abstract: Spatial filtering is one principal tool used in image processing for a broad spectrum of applications. Median filtering has become a prominent representation of spatial filtering because its performance in noise reduction is excellent. Although filtering of quantum images in the frequency domain has been described in the literature, and there is a one-to-one correspondence between linear spatial filters and filters in the frequency domain, median filtering is a nonlinear process that cannot be achieved in the frequency domain. We therefore investigated the spatial filtering of quantum image, focusing on the design method of the quantum median filter and applications in image de-noising. To this end, first, we presented the quantum circuits for three basic modules (i.e., Cycle Shift, Comparator, and Swap), and then, we design two composite modules (i.e., Sort and Median Calculation). We next constructed a complete quantum circuit that implements the median filtering task and present the results of several simulation experiments on some grayscale images with different noise patterns. Although experimental results show that the proposed scheme has almost the same noise suppression capacity as its classical counterpart, the complexity analysis shows that the proposed scheme can reduce the computational complexity of the classical median filter from the exponential function of image size n to the second-order polynomial function of image size n, so that the classical method can be speeded up.

27 citations

Journal ArticleDOI
TL;DR: In this paper, the optimal spatial filtering technique, referred to as the Minimum Variance Distortionless Response (MVDR) beamformer, was proposed to suppress sidelobes, enhance the spatial resolution of an array through narrower beamwidths, and to provide superdirective array gain at frequencies well below the design frequency of the array.
Abstract: An array of hydrophones is towed below the sea surface so as to sample the underwater acoustic pressure field in both space and time, while a land-based array of microphones is used to sense the atmospheric acoustic environment which, at the time, was dominated by a single source of broadband energy. After transformation from the time domain to the frequency domain, the sensor outputs from each array are weighted and combined in the spatial domain (beamformed) so as to produce a frequency–wave number power spectrum, which displays the power spectral density distribution of the various signal and noise sources as a joint function of frequency and wave number. The frequency-domain beamforming (or spatial filtering) process enables both conventional and optimal estimation of the frequency–wave number power spectrum. The optimal spatial filtering technique used here is commonly referred to as the Minimum Variance Distortionless Response (MVDR) beamformer which requires inversion of the observed narrow-band cross-power spectral matrix at each frequency of interest. A comparison of the frequency–wave number power spectra estimated by the two spatial filtering techniques shows that the MVDR beamformer enables the various sources of acoustic energy to be more clearly delineated in frequency–wave number space. The MVDR beamformer is a data-adaptive spatial filter which is observed to suppress sidelobes, to enhance the spatial resolution of an array through narrower beamwidths, and to provide superdirective array gain at frequencies well below the design frequency of an array. By extending the processing to include the data from another type of towed array, it is shown that frequency–wave number analysis, when incorporated with MVDR beamforming, constitutes a powerful diagnostic tool for studying the self-noise characteristics of towed arrays.

27 citations

Journal ArticleDOI
TL;DR: In this article, a mass flow detector using an open cylindrical resonator based on two microstrip patch couplers was developed using particle filter velocimetry to detect the average particulate velocity.
Abstract: A novel mass flow detector has been developed using an open cylindrical resonator based on two microstrip patch couplers. The directivity of the couplers provides a compact sensor design without loss of sensitivity. The design of a particulate mass flow detector and the algorithm to detect the average solids concentration is shown. Spatial filtering velocimetry is applied to a microstrip patch sensor in order to detect the average particulate velocity. The simultaneous detection of the velocity and the solids/air concentration from a single measurement, ensure a true mass flow detector. Subsequently, free fall measurements as well as measurements in a self contained material flow measuring system were carried out in order to prove the concept.

27 citations

Book ChapterDOI
12 Sep 2006
TL;DR: This work proposes a novel spectral filter optimization algorithm for the single trial ElectroEncephaloGraphy (EEG) classification problem, and shows how a prior knowledge can drastically improve the classification or only be misleading.
Abstract: We propose a novel spectral filter optimization algorithm for the single trial ElectroEncephaloGraphy (EEG) classification problem. The algorithm is designed to improve the classification accuracy of Common Spatial Pattern (CSP) based classifiers. The algorithm is based on a simple statistical criterion, and allows the user to incorporate any prior information one has about the spectrum of the signal. We show that with a different preprocessing, how a prior knowledge can drastically improve the classification or only be misleading. We also show a generalization of the CSP algorithm so that the CSP spatial projection can be recalculated after the optimization of the spectral filter. This leads to an iterative procedure of spectral and spatial filter update that further improves the classification accuracy, not only by imposing a spectral filter but also by choosing a better spatial projection.

27 citations

Journal ArticleDOI
TL;DR: In this article, a method is proposed to estimate the diffuse sound PSD from a set of reference signals by blocking the direct signal components, which is suitable in the presence of multiple simultaneously active speakers.
Abstract: Using a recently proposed informed spatial filter, it is possible to effectively and robustly reduce reverberation from speech signals captured in noisy environments using multiple microphones. Late reverberation can be modeled by a diffuse sound field with a time-varying power spectral density (PSD). To attain reverberation reduction using this spatial filter, an accurate estimate of the diffuse sound PSD is required. In this work, a method is proposed to estimate the diffuse sound PSD from a set of reference signals by blocking the direct signal components. By considering multiple plane waves in the signal model to describe the direct sound, the method is suitable in the presence of multiple simultaneously active speakers. The proposed diffuse sound PSD estimator is analyzed and compared to existing estimators. In addition, the performance of the spatial filter computed with the diffuse sound PSD estimate is analyzed using simulated and measured room impulse responses in noisy environments with stationary noise and non-stationary babble noise.

27 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202321
202265
202181
2020144
2019180
2018179