Spatial filter

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

Speckle photography with different pupils in a multiple-exposure scheme.

Abstract: The use of different multiple-aperture pupils for recording each image in speckle photography is proposed. The introduction of suitable spatial frequency carriers, by internally modulating imaged speckles, allows one to selectively isolate or combine the spectral content of different images into spatially separated regions in the Fourier plane. Theoretical and experimental results extend the speckle photography technique to the depiction of several specklegrams of multiple uniform in-plane displacements. In this case, because different pupils are considered for recording, the cross-correlation functions for the amplitudes and intensities in the image plane are calculated on the basis of the statistical properties of the object. Also, the ensemble-average intensity in the Fourier plane is analytically derived, and fringe visibility is investigated.

Optimization of parameters in matched spatial filter synthesis.

Abstract: Criteria are provided for the selection of various matched spatial filter (MSF) synthesis parameters: the bias exposure (E(B)); beam balance ratio (K); and spatial frequency band (f*) in which K is set. The signal-to-noise ratio (SNR) and peak intensity (I(p)) of the output correlation are used as measures of optimum correlation and a diffraction pattern sampling unit is used to insure reliable and reproducible data.

Diffractive Processing of Geophysical Data

Abstract: Processing of geophysical data can be accomplished by optical diffraction. The data are in the form of transmissive recordings, environmental photographs, or. drawings. Five analyses can be performed at or near the Fraunhofer diffraction plane with single diffraction, three analyses through spatial filtering with double diffraction, and one (correlation) with triple diffraction. Primary emphasis is on the processing of variable-density seismograms, for which a special recorder has been constructed. Spatial filtering has also been applied to cloud cover pictures and contour maps.

Integrated Sidelobe Cancellation and Linear Prediction Kalman Filter for Joint Multi-Microphone Speech Dereverberation, Interfering Speech Cancellation, and Noise Reduction

Abstract: In multi-microphone speech enhancement, reverberation as well as additive noise and/or interfering speech are commonly suppressed by deconvolution and spatial filtering, e.g., using multi-channel linear prediction (MCLP) on the one hand and beamforming, e.g., a generalized sidelobe canceler (GSC), on the other hand. In this article, we consider several reverberant speech components, whereof some are to be dereverberated and others to be canceled, as well as a diffuse (e.g., babble) noise component to be suppressed. In order to perform both deconvolution and spatial filtering, we integrate MCLP and the GSC into a novel architecture referred to as integrated sidelobe cancellation and linear prediction (ISCLP), where the sidelobe-cancellation (SC) filter and the linear prediction (LP) filter operate in parallel, but on different microphone signal frames. Within ISCLP, we estimate both filters jointly by means of a single Kalman filter. We further propose a spectral Wiener gain post-processor, which is shown to relate to the Kalman filter's posterior state estimate. The presented ISCLP Kalman filter is benchmarked against two state-of-the-art approaches, namely first a pair of alternating Kalman filters respectively performing dereverberation and noise reduction, and second an MCLP+GSC Kalman filter cascade. While the ISCLP Kalman filter is roughly $M^2$ times less expensive than both reference algorithms, where $M$ denotes the number of microphones, it is shown to perform at least similarly as compared to the former, and to outperform the latter. A MATLAB implementation is available.

Digital imaging using a scanning mirror apparatus

Abstract: Method and apparatus for generating a large-field, high-resolution digital image of an object by sequentially generating multiple optical scenes representative of different portions of the object, and then sequentially directing each optical scene onto an optical detector to generate multiple sub-images of the different portions of the object. Each scene is induced using a separate X-ray sub-beam, each of which is generated by spatially filtering a portion of an incident X-ray field with a spatial filter moving in concert with the scene-directing device. Once generated, the sub-images are combined to form the large-field, high-resolution image.