Effect on Noise of Intensity-Axis Correction of Spectra Recorded with Charge-Coupled Device Detectors

2002 ◽  
Vol 56 (5) ◽  
pp. 564-569 ◽  
Author(s):  
Jay Pendell Jones ◽  
Ronald E. Wambles ◽  
Charles K. Mann ◽  
Thomas J. Vickers

We have examined the effect of intensity-axis correction on noise in white light spectra recorded with charge-coupled device (CCD) detectors. Measurements were made with five detectors in Raman spectrometers. Detectors were both liquid-nitrogen and thermoelectrically cooled devices and one room temperature device. Both random and pattern noise have been considered. We used cross-correlation of noise sets to provide an indicator of a fixed pattern in the spectra and an assessment of the efficacy of the correction procedure in removing this pattern. For four of the five detectors intensity-axis correction provided a significant improvement in signal-to-noise ratio. Correction was particularly important for measurements made with lower-cost CCD detectors of the kind proposed for process control instruments.

2018 ◽  
Author(s):  
Darren Whitaker ◽  
Kevin Hayes

Raman Spectroscopy is a widely used analytical technique, favoured when molecular specificity with minimal sample preparation is required.<br>The majority of Raman instruments use charge-coupled device (CCD) detectors, these are susceptible to cosmic rays and as such multiple spurious spikes can occur in the measurement. These spikes are problematic as they may hinder subsequent analysis, particularly if multivariate data analysis is required. In this work we present a new algorithm to remove these spikes from spectra after acquisition. Specifically we use calculation of modified <i>Z</i> scores to locate spikes followed by a simple moving average filter to remove them. The algorithm is very simple and its execution is essentially instantaneous, resulting in spike-free spectra with minimal distortion of actual Raman data. The presented algorithm represents an improvement on existing spike removal methods by utilising simple, easy to understand mathematical concepts, making it ideal for experts and non-experts alike. <br>


2018 ◽  
Author(s):  
Darren Whitaker ◽  
Kevin Hayes

Raman Spectroscopy is a widely used analytical technique, favoured when molecular specificity with minimal sample preparation is required.<br>The majority of Raman instruments use charge-coupled device (CCD) detectors, these are susceptible to cosmic rays and as such multiple spurious spikes can occur in the measurement. These spikes are problematic as they may hinder subsequent analysis, particularly if multivariate data analysis is required. In this work we present a new algorithm to remove these spikes from spectra after acquisition. Specifically we use calculation of modified <i>Z</i> scores to locate spikes followed by a simple moving average filter to remove them. The algorithm is very simple and its execution is essentially instantaneous, resulting in spike-free spectra with minimal distortion of actual Raman data. The presented algorithm represents an improvement on existing spike removal methods by utilising simple, easy to understand mathematical concepts, making it ideal for experts and non-experts alike. <br>


2018 ◽  
Author(s):  
Darren Whitaker ◽  
Kevin Hayes

Raman Spectroscopy is a widely used analytical technique, favoured when molecular specificity with minimal sample preparation is required.<br>The majority of Raman instruments use charge-coupled device (CCD) detectors, these are susceptible to cosmic rays and as such multiple spurious spikes can occur in the measurement. These spikes are problematic as they may hinder subsequent analysis, particularly if multivariate data analysis is required. In this work we present a new algorithm to remove these spikes from spectra after acquisition. Specifically we use calculation of modified <i>Z</i> scores to locate spikes followed by a simple moving average filter to remove them. The algorithm is very simple and its execution is essentially instantaneous, resulting in spike-free spectra with minimal distortion of actual Raman data. The presented algorithm represents an improvement on existing spike removal methods by utilising simple, easy to understand mathematical concepts, making it ideal for experts and non-experts alike. <br>


Author(s):  
Wenjun Huo ◽  
Peng Chu ◽  
Kai Wang ◽  
Liangting Fu ◽  
Zhigang Niu ◽  
...  

In order to study the detection methods of weak transient electromagnetic radiation signals, a detection algorithm integrating generalized cross-correlation and chaotic sequence prediction is proposed in this paper. Based on the dual-antenna test and cross-correlation information estimation method, the detection of aperiodic weak discharge signals under low signal-to-noise ratio is transformed into the estimation of periodic delay parameters, and the noise is reduced at the same time. The feasibility of this method is verified by simulation and experimental analysis. The results show that under the condition of low signal-to-noise ratio, the integrated method can effectively suppress the influence of 10 noise disturbances. It has a high detection probability for weak transient electromagnetic radiation signals, and needs fewer pulse accumulation times, which improves the detection efficiency and is more suitable for long-distance detection of weak electromagnetic radiation sources.


2013 ◽  
Vol 9 (S304) ◽  
pp. 243-243
Author(s):  
Takamitsu Miyaji ◽  
M. Krumpe ◽  
A. Coil ◽  
H. Aceves ◽  
B. Husemann

AbstractWe present the results of our series of studies on correlation function and halo occupation distribution of AGNs utilizing data the ROSAT All-Sky Survey (RASS) and the Sloan Digital Sky Survey (SDSS) in the redshift range of 0.07<z<0.36. In order to improve the signal-to-noise ratio, we take cross-correlation approach, where cross-correlation functions (CCF) between AGNs and much more numerous AGNs are analyzed. The calculated CCFs are analyzed using the Halo Occupation Distribution (HOD) model, where the CCFs are divided into the term contributed by the AGN-galaxy pairs that reside in one dark matter halo (DMH), (the 1-halo term) and those from two different DMHs (the 2-halo term). The 2-halo term is the indicator of the bias parameter, which is a function of the typical mass of the DMHs in which AGNs reside. The combination of the 1-halo and 2-halo terms gives, not only the typical DMH mass, but also how the AGNs are distributed among the DMHs as a function of mass separately for those at the center of the DMHs and satellites. The main results are as follows: (1) the range of typical mass of the DMHs in various sub-samples of AGNs log (MDMH/h−1MΘ) ~ 12.4–13.4, (2) we found a dependence of the AGN bias parameter on the X-ray luminosity of AGNs, while the optical luminosity dependence is not significant probably due to smaller dynamic range in luminosity for the optically-selected sample, and (3) the growth of the number of AGNs per DMH (N (MDMH)) with MDMH is shallow, or even may be flat, contrary to that of the galaxy population in general, which grows with MDMH proportionally, suggesting a suppression of AGN triggering in denser environment. In order to investigate the origin of the X-ray luminosity dependence, we are also investigating the dependence of clustering on the black hole mass and the Eddington ratio, we also present the results of this investigation.


2004 ◽  
Vol 04 (02) ◽  
pp. L247-L265 ◽  
Author(s):  
ARUNEEMA DAS ◽  
N. G. STOCKS ◽  
A. NIKITIN ◽  
E. L. HINES

We explore stochastic resonance (SR) effects in a single comparator (threshold detector) driven by either a Gaussian or exponentially distributed aperiodic signal. The behaviour of different performance measures, namely the cross-correlation coefficient (CCC), signal-to-noise ratio (SNR) and mutual information, I, has been investigated. The signals were added to Gaussian noise before being passed through the threshold detector. For the two signals tested, we observe the perhaps surprising result that the SNR never displays SR. However, SR is displayed by both the CCC and I for Gaussian signals. For exponential signals SR is not displayed by any of the measures. By generating signals whose probability distributions have the generalized Gaussian form Ae-|βx|n it is possible to demonstrate that SR ceases to occur if n<1.7. We conclude that SR is only observable in threshold based systems for certain types of aperiodic signal. Specifically, SR is not expected to occur for signals whose probability density functions have long, slowly decaying, tails. We discuss the implication of these results for the role of SR in biological sensory systems.


Author(s):  
Jinshan Cao ◽  
Xiuxiao Yuan ◽  
Jianya Gong

Due to the large biases between the laboratory-calibrated values of the orientation parameters and their in-orbit true values, the initial direct georeferencing accuracy of the Ziyuan-3 (ZY-3) three-line camera (TLC) images can only reach the kilometre level. In this paper, a point-based geometric calibration model of the ZY-3 TLCs is firstly established by using the collinearity constraint, and then a line-based geometric calibration model is established by using the coplanarity constraint. With the help of both the point-based and the line-based models, a feasible in-orbit geometric calibration approach for the ZY-3 TLCs combining ground control points (GCPs) and ground control lines (GCLs) is presented. Experimental results show that like GCPs, GCLs can also provide effective ground control information for the geometric calibration of the ZY-3 TLCs. The calibration accuracy of the look angles of charge-coupled device (CCD) detectors achieved by using the presented approach reached up to about 1.0''. After the geometric calibration, the direct georeferencing accuracy of the ZY-3 TLC images without ground controls was significantly improved from the kilometre level to better than 11 m in planimetry and 9 m in height. A more satisfactory georeferencing accuracy of better than 3.5 m in planimetry and 3.0 m in height was achieved after the block adjustment with four GCPs.


Author(s):  
Michael Radermacher ◽  
Teresa Ruiz

Biological samples are radiation-sensitive and require imaging under low-dose conditions to minimize damage. As a result, images contain a high level of noise and exhibit signal-to-noise ratios that are typically significantly smaller than 1. Averaging techniques, either implicit or explicit, are used to overcome the limitations imposed by the high level of noise. Averaging of 2D images showing the same molecule in the same orientation results in highly significant projections. A high-resolution structure can be obtained by combining the information from many single-particle images to determine a 3D structure. Similarly, averaging of multiple copies of macromolecular assembly subvolumes extracted from tomographic reconstructions can lead to a virtually noise-free high-resolution structure. Cross-correlation methods are often used in the alignment and classification steps of averaging processes for both 2D images and 3D volumes. However, the high noise level can bias alignment and certain classification results. While other approaches may be implicitly affected, sensitivity to noise is most apparent in multireference alignments, 3D reference-based projection alignments and projection-based volume alignments. Here, the influence of the image signal-to-noise ratio on the value of the cross-correlation coefficient is analyzed and a method for compensating for this effect is provided.


The target of the registration process is to get the disagreement between two captured images for the same area to candidate the transformation matrix that is used to map the points in one image to its congruent in the other image for the same area. A dynamic method is demonstrated in this paper to improve registration process of SAR images. At first, smoothing filtering is used for noise reduction based on gaussian-kernel filter to set aside the pursue-up amplification of noise. Then; area based matching method, cross correlation, is used to perform a coarse registration. The output of the coarse registration is directly applied to the regular step gradient descent (RSGD) optimizer as a fine registration process. The performance of the demonstrated method was evaluated via comparison with the common used corner detectors (Harris, Minimum Eigenvalues, and FAST). Mean square error (MSE) and peak signal-to-noise ratio (PSNR) are the main factors for the comparison. The results show that the demonstrated approach preserves the robustness of the registration process and minimizes the image noise.


2016 ◽  
Vol 71 (5) ◽  
pp. 988-995 ◽  
Author(s):  
Patrick D. Barnett ◽  
S. Michael Angel

A spatial heterodyne Raman spectrometer (SHRS) with millimeter-sized optics has been coupled with a standard cell phone camera as a detector for Raman measurements. The SHRS is a dispersive-based interferometer with no moving parts and the design is amenable to miniaturization while maintaining high resolution and large spectral range. In this paper, a SHRS with 2.5 mm diffraction gratings has been developed with 17.5 cm−1 theoretical spectral resolution. The footprint of the SHRS is orders of magnitude smaller than the footprint of charge-coupled device (CCD) detectors typically employed in Raman spectrometers, thus smaller detectors are being explored to shrink the entire spectrometer package. This paper describes the performance of a SHRS with 2.5 mm wide diffraction gratings and a cell phone camera detector, using only the cell phone’s built-in optics to couple the output of the SHRS to the sensor. Raman spectra of a variety of samples measured with the cell phone are compared to measurements made using the same miniature SHRS with high-quality imaging optics and a high-quality, scientific-grade, thermoelectrically cooled CCD.


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