Two-dimensional Wiener Filter Research Articles

Reference Signal Design and Power Optimization for Energy-Efficient 5G V2X Integrated Sensing and Communications

Recently, the development of integrated sensing and communications (ISAC) has attracted great attention. In this paper, the reference signal (RS) in 5G vehicle-to-everything (V2X) communications is leveraged for radar sensing. Particularly, the scattered RS design is adopted under the constraints of communication channel estimation and radar sensing ambiguity functions. To quantify the influence of RS design on channel estimation, the minimum mean square error (MMSE) via two-dimensional Wiener filter is derived in a closed-form for doubly-selective communication channel. The RS spacing and power allocation for RS and each data subcarrier are further jointly optimized to minimize the transmission power, while satisfying the requirements of communication data rate and radar sensing signal to noise ratio (SNR), which results in a mixed-integer non-linear programming (MINLP) problem. To address this problem, the successive convex approximation (SCA) based method is first developed to achieve a suboptimal solution. Next, we show that if the RS spacing is given, the optimal power allocation among RS and each data subcarrier can be achieved by solving three subproblems sequentially via (reverse) water-filling algorithms. Extensive simulations are carried out to validate the effectiveness of our proposed design. Compared to the existing subcarrier-wise RS design with uniform power allocation for data subcarriers, our design can reduce the power consumption by up to 12 dB.

Enhancing spatial resolution of BOTDR sensors using image deconvolution.

We propose to employ the image deconvolution technique for Brillouin optical time domain reflectometry (BOTDR) systems to achieve a flexible and enhanced spatial resolution with pump pulses longer than phonon lifetime. By taking the measured Brillouin gain spectrum (BGS) distribution as an image blurred by a point spread function (PSF), the image deconvolution algorithm based on the two-dimensional Wiener filtering can mitigate the ambiguity effect on the Brillouin response. The deconvoluted BGS distribution reveals detailed sensing information within shorter fiber segments, improving the inferior spatial resolution and simultaneously maintaining other sensing performance parameters. Thanks to the proposed technique, a typical BOTDR sensor with 40 ns pump pulses reaches a submetric spatial resolution as high as 10 cm. Compared to the differential-spectrum-based BOTDR retrieving the same spatial resolution, the image deconvolution technique shows advantages in system complexity and measurement uncertainty. Moreover, the proposed technique is promising to improve the spatial resolution of other distributed optical fiber sensing (DOFS) techniques such as BOTDR systems with complex pump modulation methods.

Time-frequency readability enhancement of compact support kernel-based distributions using image post-processing: Application to instantaneous frequency estimation of M-ary frequency shift keying signals

Time-frequency distributions (TFDs) based on time-lag kernels with compact support (KCS) have proved their high performance in terms of resolution and crossterms suppression. However, as for all kernel-based quadratic TFDs, these distributions suffer from spreading out signal terms. This is due to the unavoidable smoothing effects of the kernel in the ambiguity domain. The main objective of this paper is to improve concentration, interference rejection and so time-frequency localization of this representation class. The latter has the advantage of being tuned using a single parameter while external windows are no longer needed. The KCS-TFDs, referred to as KCSDs, are first optimized using a selection of the most used objective performance measures in the literature. Important signal features are extracted as well through analysis of time slice plots. The obtained TF diagrams are then enhanced using a specific method that includes two-dimensional Wiener filter, automatic binarization and morphological image processing techniques. The enhanced plots are compared to those obtained from the original TFDs using several tests on real-life and multicomponent frequency modulated (FM) signals including the noise effects. Moreover, a comparative study involving a selection of the best-performing reassignment time-frequency distributions is provided. The obtained results show a significant improvement of concentration, time-frequency localization of the autoterms as well as interference and noise suppression. As viable applications, the proposed approach is used first to instantaneous frequency (IF) estimation of several synthetic and real-life M-ary frequency shift keying (MFSK) signals. It is shown that the IF estimator from the enhanced plots performs better than smoothed pseudo Wigner-Ville distribution (SPWVD) and reassignment post-processing-based TFDs in terms of mainlobe width (MLW) and variance, respectively, even at low signal-to-noise ratio (SNR). On the other hand, time-frequency characterization of continuous wave linear frequency modulation (CW-LFM) and pulse linear FM (PLFM) radar signals is also investigated.

Quantification of phase-based magnified motion using image enhancement and optical flow techniques

Phase-based motion magnification (PMM) has been widely implemented in the field of vibration and structural health monitoring for its non-invasive nature to reveal hidden system dynamics. The approach has shown success in magnifying subtle structural oscillatory motions for system identification and observation of operating shapes. Although this method has been implemented and is becoming increasingly popular, the amount of physical motion associated with the degree of magnification has yet to be quantified. Within this work, a synthetic simulation containing an oscillating geometry is presented to quantify its magnified pixel displacement. Computer vision techniques including centroid detection and edge-feature tracking via optical flow are adopted to quantify the relation between amplification and true motion. The quantification techniques are also tested and verified on an experimental structure with the use of a high-speed optical sensing system. Motion artifacts distort the integrity of the magnified motion, which can pose problems for accurate quantification. Image enhancement techniques such as the two-dimensional Wiener filter and Total Variation Denoising (TVD) are used to smooth the high-frequency content that is observed following magnification. Associative error concerning a discrete shift of the Gabor wavelet is analytically derived to show the justification of spatial aliasing. An adjusted bound on magnification is presented to display the limitations of the technique, while providing insight into associated error. The results of this work will help to enhance PMM from a qualitative evaluation tool to a quantitative measurement tool of magnified displacements.

INFLUENCE OF DIGITAL IMAGES PRELIMINARY NOISING ON STATISTICAL STEGDETECTORS PERFORMANCE

Context. The problem of sensitive information protection during data transmission in communication systems was considered. The case of reliable detection of stego images formed according to advanced embedding methods was investigated. The object of research is digital images steganalysis of adaptive steganographic methods.
 Objective. The goal of the work is performance analysis of statistical stegdetectors for adaptive embedding methods in case of preliminary noising of analyzed image with thermal and shot noises.
 Method. The image pre-processing (calibration) method was proposed for improving stego-to-cover ratio for state-of-the-art adaptive embedding methods HUGO, MG and MiPOD. The method is aimed at amplifying negligible changes of cover image caused by message hiding with usage of Gaussian and Poisson noises. The former one is related to influence the thermal noise of chargecoupled device (CCD) based image sensor during data acquisition. The latter one is related to shot noise that originates from stochastic process of electron emission by photons hitting of CCD elements. During the research, parameters of thermal noise were estimated with two-dimensional Wiener filter, while sliding window of size 5·5 pixels was used for parameters evaluation for shot noise.
 Results. The dependencies of detection error on cover image payload for advance HUGO, MG and MiPOD embedding methods were obtained. The results were presented for the case of image pre-noising with both Gaussian and Poisson noises, and varying of feature pre-processing methods.
 Conclusions. The conducted experiments confirmed effectiveness of proposed approach for image calibration with Poisson noise. Obtained results allow us to recommend linearly transformed features to be used for improving stegdetector performance by natural image processing. The prospects for further research may include investigation usage of special noises, such as fractal noises, for improving stego-to-cover ratio for advanced embedding methods.

Adaptive wiener filter based chrominance up-sampling enhancement method for video coding

In order to improve the quality of the reconstructed video, the Wiener filter is employed in video coding to reduce the distortion caused by chrominance down/up sampling and encoding. Based on the mathematical analysis, it is verified that the distortion introduced by chrominance sampling and coding can be approximately treated as a wide sense stationary noise, which can be suppressed by the Wiener filter. Accordingly, in this paper, a two-dimensional Wiener filter is designed for reducing the noise of the reconstructed chrominance components, which further improves the video quality in the RGB color space as finally perceived by the users. Experimental results show that compared with bi-linear and inter-color up-sampling, the proposed method achieves the average gains of 0.42 dB and 0.30 dB, respectively. Meanwhile, the reconstructed video obtained by the proposed method is more close to the original one in terms of subjective quality <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> .

Radio Frequency Interference Detection and Mitigation Algorithms Based on Spectrogram Analysis

Radio Frequency Interference (RFI) detection and mitigation algorithms based on a signal’s spectrogram (frequency and time domain representation) are presented. The radiometric signal’s spectrogram is treated as an image, and therefore image processing techniques are applied to detect and mitigate RFI by two-dimensional filtering. A series of Monte-Carlo simulations have been performed to evaluate the performance of a simple thresholding algorithm and a modified two-dimensional Wiener filter.

Toward automated quality assurance for intensity- modulated radiation therapy

Purpose: To investigate whether high-quality, relatively inexpensive, document and transparency scanners used as densitometers are sufficiently quantitative for routine quality assurance (QA).Methods and Materials: The scanner we investigated used a linear amplifier, digitizing gray-scale images to 12-bit resolution with a user-selected spatial resolution of 0.170 mm2 pixels. To reduce Newton’s rings artifacts, the standard glass platen was replaced by glass with an antireflective coating. Conversion of reading to transmission was conducted by permanently placing a calibrated photographic step tablet on the scanner platen. After conversion to light transmission, a zero-phase two-dimensional Wiener filter was used to reduce pixel-to-pixel signal variation. Light-scatter artifacts were removed by deconvolution of a measured light-spread kernel. The light-spread kernel artifacts were significant along the scanner’s detector axis, but were insignificant along the scanning axis.Results: Pixel-to-pixel noise was better than 2% for optical densities, ranging from 0.4 to 2.0 and 0 to 2.7 for the unfiltered and filtered images, respectively. The document scanning system response was compared against a confocal scanning laser densitometer. A series of IMRT dose distribution and dose calibration film sets were scanned using the two scanners, and the measured dose was compared. The maximum mean and standard deviation of the measured dose difference between the document scanner and confocal scanner was 1.48% and 1.06%, respectively.Conclusion: While the document scanners are not as flexible as dedicated film densitometers, these results indicate that, using the intensity and scatter corrections, the system provides accurate and precise measurements up to an optical density of 2.0, sufficient for routine IMRT film QA. For some film types, this requires the reduction in monitor units to limit the dose delivered to the film. The user must be cautious that the delivered IMRT dose is scaled appropriately. This inexpensive and accurate system is being integrated into an automated QA program.

An adaptive two-dimensional channel estimator for wireless OFDM with application to mobile DVB-T

An adaptive channel estimator is proposed and investigated to improve the performance of the receiver for pilot aided wireless and mobile OFDM systems. The estimator consists of a two-dimensional Wiener filter which is implemented as a cascade of two one-dimensional filters. We propose an efficient algorithm for adaptation to time varying channels of the second filter. The method is applied to the Terrestrial Digital Video Broadcasting System (DVB-T), which was originally specified for fixed receivers and which is in the process of being extended for mobile reception. The results are shown after inner decoding. Depending on the channel conditions, the signal-to-noise ratio gain can be up to 1.6 dB. The method provides a compatible improvement to DVB-T receivers.

Image Multimodeling and a Two-Dimensional Multicategory Wiener Filter

The nonstationarity of images and the lack of a factorization theorem in two dimensions make the implementation of recursive imagerestoration procedures very difficult. A restoration procedure that partially avoids these issues by modeling the image differently is presented. The image is decomposed into additive components, and each one is modeled as a second-order random process with a separable exponential autocovariance and a constant mean. These components are obtained by means of a masking function relating the regional luminance in the image and the image sensitivity to noise. The present model facilitates the application of a two-dimensional Wiener filter in the form of a bank of filters. A restoration example illustrating the issues involved is given.

International Planetary Patrol observations of Saturn's rings. I - Observations and data reduction

view Abstract Citations (4) References (8) Co-Reads Similar Papers Volume Content Graphics Metrics Export Citation NASA/ADS International Planetary Patrol observations of Saturn's rings. I. Observations and data reduction. Lumme, K. ; Esposito, L. W. ; Benton, W. D. ; Baum, W. A. Abstract The paper describes the reduction procedure used for observations of Saturn's rings taken with the International Planetary Patrol Network in 1977. Corrections for atmospheric smearing are determined using an assumed ring model and performed by a two-dimensional Wiener filter developed at JPL's Image Processing Laboratory. These smearing corrections are shown to be consistent with the radial profile of the rings, not just on the major axis of the ring system, but over a range of azimuthal angle. Publication: The Astronomical Journal Pub Date: September 1979 DOI: 10.1086/112558 Bibcode: 1979AJ.....84.1402L Keywords: Astronomical Observatories; Data Reduction; Image Processing; International Cooperation; Saturn Rings; Light Scattering; Patrols; Radar Imagery; Telescopes; Wiener Filtering; SATURN; RINGS; OBSERVATIONS; DATA REDUCTION; PHOTOMETRY; MODELS; STRUCTURE; COMPOSITION; SIZE; EQUIPMENT; MICRODENSITOMETER; PROCEDURE; PARAMETERS; Lunar and Planetary Exploration; Saturn; Image Processing:Saturn Rings full text sources ADS |

A Fast Karhunen-Loeve Transform for Digital Restoration of Images Degraded by White and Colored Noise

The Karhunen-Loeve (KL) transform is known to have certain properties which make it optimal for many mean-square signal processing applications [1]-[4]. Recently, it has been shown that a class of digital images may be represented by a set of boundary value stochastic difference equations in two dimensions [5]-[7]. If the boundary conditions of this class of images are fixed, then these equations lead to a fast KL transform algorithm. Here this fast KL transform is used for Wiener filtering of images degraded by white or colored noise. Comparisons with Generalized Wiener Filtering [1] and conventional Fourier domain filtering are made. It is shown that the two-dimensional Wiener filter is nonseparable so that two-dimensional generalized Wiener filtering is more elaborate than reported in [1]. It is also shown that certain fast KL filters give better signal-to-noise ratio than the conventional Fourier domain Wiener filter and enable determination of an easily computable performance bound. Recursive filtering equations for implementing the fast KL filter on two-dimensional images including both white and colored noise cases are given. These results show that recursive filtering algorithms for images are faster than the transform-domain algorithms and the one-step interpolator algorithm performs very close to the smoothing filter and can be implemented online by introducing a one-step delay.

Spatial Filtering for Noise Reduction in a Multirecording Telecine System

The purpose is to determine the transfer function of the two-dimensional Wiener filter in a color telecine system using multirecorded monochrome photographic film in which three-color information of an object is recorded separately with different spatial frequency regions. According to theory, the S/N of a high frequency carrier signal is improved approximately 10 dB with the Wiener filter, A Wiener filter is produced by introducing a coherent spatial filtering optical system into the telecine system. Satisfactory results were obtained in the filtering experiments on actual production of the Wiener filter.