scholarly journals Improving the quality of empirical Green's functions, obtained by cross-correlation of high-frequency ambient seismic noise

Solid Earth ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 1621-1634 ◽  
Author(s):  
Nikita Afonin ◽  
Elena Kozlovskaya ◽  
Jouni Nevalainen ◽  
Janne Narkilahti
Keyword(s):  
High Frequency ◽  
Seismic Noise ◽  
Cross Correlation ◽  
Signal To Noise Ratio ◽  
Ambient Seismic Noise ◽  
Signal To Noise ◽  
Seismic Methods ◽  
Noise Ratio ◽  
High Level

Abstract. Studying the uppermost structure of the subsurface is a necessary part of solving many practical problems (exploration of minerals, groundwater studies, geoengineering, etc.). The practical application of active seismic methods for these purposes is not always possible for different reasons, such as logistical difficulties, high cost of work, and a high level of seismic and acoustic noise. That is why developing and improving passive seismic methods is one of the important problems in applied geophysics. In our study, we describe a way of improving the quality of empirical Green's functions (EGFs), evaluated from high-frequency ambient seismic noise, by using the advanced technique of cross-correlation function stacking in the time domain (in this paper we use term “high-frequency” for frequencies higher than 1 Hz). The technique is based on the global optimization algorithm, in which the optimized objective function is a signal-to-noise ratio of an EGF, retrieved at each iteration. In comparison to existing techniques, based, for example, on weight stacking of cross-correlation functions, our technique makes it possible to significantly increase the signal-to-noise ratio and, therefore, the quality of the EGFs. The technique has been tested with the field data acquired in an area with a high level of industrial noise (Pyhäsalmi Mine, Finland) and in an area with a low level of anthropogenic noise (Kuusamo Greenstone Belt, Finland). The results show that the proposed technique can be used for the extraction of EGFs from high-frequency seismic noise in practical problems of mapping of the shallow subsurface, both in areas with high and low levels of high-frequency seismic noise.

scholarly journals Improving quality of empirical Greens functions, obtained by cross-correlation of high-frequency ambient seismic noise

2019 ◽  
Author(s):  
Nikita Afonin ◽  
Elena Kozlovskaya ◽  
Jouni Nevalainen ◽  
Janne Narkilahti
Keyword(s):  
High Frequency ◽  
Seismic Noise ◽  
Cross Correlation ◽  
Signal To Noise Ratio ◽  
Ambient Seismic Noise ◽  
Signal To Noise ◽  
Low Level ◽  
Seismic Methods ◽  
High Level

Abstract. Studying the uppermost structure of the subsurface is a necessary part for solving many practical problems (exploration of minerals, groundwater studies, geoengineering, etc.). Practical application of active seismic methods is not always possible because of different reasons, such as logistical difficulties, high cost of work, high level of seismic and acoustic noise, etc. That is why developing and improving of passive seismic methods for these purposes is one of the important problems in applied geophysics. In our study, we describe the way of improving quality of Empirical Green’s Functions (EGFs), evaluated from high-frequency ambient seismic noise, by using of advanced technique of cross-correlation functions stacking in the time domain (in this paper we use term “high-frequency” for the frequencies higher than 1 Hz). In compare to existing techniques, based on weight-stacking, our proposed technique makes it possible to more significantly increase the signal-to-noise ratio and, therefore quality of the EGF. The technique is based on both iterative and global optimization algorithms, where the optimized parameter is a signal-to-noise ratio of an EGF, retrieved for each iteration. The technique has been tested with the field data acquired in an area with high level of industrial noise (Pyhäsalmi Mine, Finland) and in an area with low level of anthropogenic noise (Kuusamo Greenstone Belt, Finland). The results show that the our proposed technique can be used for extraction of EGFs from high-frequency seismic noise in practical problems of mapping of the shallow subsurface in areas with high and low level of high-frequency seismic noise.

Image Quality Enhancing by Efficient Histogram Equalization

2014 ◽  
Vol 2 (2) ◽  
pp. 47-58
Author(s):  
Ismail Sh. Baqer
Keyword(s):  
Image Quality ◽  
Contrast Enhancement ◽  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Histogram Equalization ◽  
Gray Level ◽  
Signal To Noise ◽  
Squared Error ◽  
Noise Ratio

A two Level Image Quality enhancement is proposed in this paper. In the first level, Dualistic Sub-Image Histogram Equalization DSIHE method decomposes the original image into two sub-images based on median of original images. The second level deals with spikes shaped noise that may appear in the image after processing. We presents three methods of image enhancement GHE, LHE and proposed DSIHE that improve the visual quality of images. A comparative calculations is being carried out on above mentioned techniques to examine objective and subjective image quality parameters e.g. Peak Signal-to-Noise Ratio PSNR values, entropy H and mean squared error MSE to measure the quality of gray scale enhanced images. For handling gray-level images, convenient Histogram Equalization methods e.g. GHE and LHE tend to change the mean brightness of an image to middle level of the gray-level range limiting their appropriateness for contrast enhancement in consumer electronics such as TV monitors. The DSIHE methods seem to overcome this disadvantage as they tend to preserve both, the brightness and contrast enhancement. Experimental results show that the proposed technique gives better results in terms of Discrete Entropy, Signal to Noise ratio and Mean Squared Error values than the Global and Local histogram-based equalization methods

Singular Values Decomposition and Lifting Wavelet Transform for Speech Signal Embedding into Digital Image

2019 ◽  
Vol 12 (2) ◽  
pp. 138-151
Author(s):  
Mourad Talbi ◽  
Med Salim Bouhlel
Keyword(s):  
Wavelet Transform ◽  
Speech Signal ◽  
Signal To Noise Ratio ◽  
Perceptual Quality ◽  
Lifting Wavelet Transform ◽  
Signal To Noise ◽  
Perceptual Evaluation ◽  
Lifting Wavelet ◽  
Noise Ratio

Background: In this paper, we propose a secure image watermarking technique which is applied to grayscale and color images. It consists in applying the SVD (Singular Value Decomposition) in the Lifting Wavelet Transform domain for embedding a speech image (the watermark) into the host image. Methods: It also uses signature in the embedding and extraction steps. Its performance is justified by the computation of PSNR (Pick Signal to Noise Ratio), SSIM (Structural Similarity), SNR (Signal to Noise Ratio), SegSNR (Segmental SNR) and PESQ (Perceptual Evaluation Speech Quality). Results: The PSNR and SSIM are used for evaluating the perceptual quality of the watermarked image compared to the original image. The SNR, SegSNR and PESQ are used for evaluating the perceptual quality of the reconstructed or extracted speech signal compared to the original speech signal. Conclusion: The Results obtained from computation of PSNR, SSIM, SNR, SegSNR and PESQ show the performance of the proposed technique.

Weak Transient Electromagnetic Radiation Signal Detection Method Considering the New Watershed Image Segmentation Algorithm

2019 ◽  
Vol 34 (03) ◽  
pp. 2054009
Author(s):  
Wenjun Huo ◽  
Peng Chu ◽  
Kai Wang ◽  
Liangting Fu ◽  
Zhigang Niu ◽  
...  
Keyword(s):  
Electromagnetic Radiation ◽  
Cross Correlation ◽  
Detection Efficiency ◽  
Signal To Noise Ratio ◽  
Estimation Method ◽  
Detection Methods ◽  
Signal To Noise ◽  
Long Distance ◽  
Transient Electromagnetic ◽  
Noise Ratio

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.

scholarly journals On cross-correlations, averages and noise in electron microscopy

2019 ◽  
Vol 75 (1) ◽  
pp. 12-18 ◽  
Author(s):  
Michael Radermacher ◽  
Teresa Ruiz
Keyword(s):  
High Resolution ◽  
Cross Correlation ◽  
Signal To Noise Ratio ◽  
3D Structure ◽  
Signal To Noise ◽  
High Resolution Structure ◽  
Multiple Copies ◽  
High Level ◽  
2D Images ◽  
Resolution Structure

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.

scholarly journals Encryption Based Image Watermarking Algorithm in 2DWT-DCT Domains

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5540
Author(s):  
Nayeem Hasan ◽  
Md Saiful Islam ◽  
Wenyu Chen ◽  
Muhammad Ashad Kabir ◽  
Saad Al-Ahmadi
Keyword(s):  
Signal To Noise Ratio ◽  
Image Watermarking ◽  
Similarity Index ◽  
Structural Similarity ◽  
Reconstructed Image ◽  
Discrete Wavelet ◽  
Signal To Noise ◽  
Noise Ratio ◽  
Watermarking Scheme

This paper proposes an encryption-based image watermarking scheme using a combination of second-level discrete wavelet transform (2DWT) and discrete cosine transform (DCT) with an auto extraction feature. The 2DWT has been selected based on the analysis of the trade-off between imperceptibility of the watermark and embedding capacity at various levels of decomposition. DCT operation is applied to the selected area to gather the image coefficients into a single vector using a zig-zig operation. We have utilized the same random bit sequence as the watermark and seed for the embedding zone coefficient. The quality of the reconstructed image was measured according to bit correction rate, peak signal-to-noise ratio (PSNR), and similarity index. Experimental results demonstrated that the proposed scheme is highly robust under different types of image-processing attacks. Several image attacks, e.g., JPEG compression, filtering, noise addition, cropping, sharpening, and bit-plane removal, were examined on watermarked images, and the results of our proposed method outstripped existing methods, especially in terms of the bit correction ratio (100%), which is a measure of bit restoration. The results were also highly satisfactory in terms of the quality of the reconstructed image, which demonstrated high imperceptibility in terms of peak signal-to-noise ratio (PSNR ≥ 40 dB) and structural similarity (SSIM ≥ 0.9) under different image attacks.

Picking noisy refraction data using semblance supplemented by a Monte Carlo procedure and spectral balancing

1987 ◽  
Vol 77 (3) ◽  
pp. 942-957
Author(s):  
C. A. Zelt ◽  
J. J. Drew ◽  
M. J. Yedlin ◽  
R. M. Ellis
Keyword(s):  
Monte Carlo ◽  
Cross Correlation ◽  
Signal To Noise Ratio ◽  
Time Shift ◽  
Head Wave ◽  
Signal To Noise ◽  
Seismic Section ◽  
Monte Carlo Procedure ◽  
Noise Ratio ◽  
Refraction Data

Abstract In crustal refraction experiments, the crucial deeply refracted and head wave arrivals often have a low signal-to-noise ratio. A method to aid in the picking of noisy refraction data is presented which is applicable to any branch of a seismic section whose waveform is approximately invariant throughout the branch. The technique exploits the spatial correlation of arrivals and is based on the lateral coherency which results if the refracted arrivals are aligned by applying appropriate time shifts to each trace of the branch. The alignment of arrivals occurs iteratively and is accomplished through a cross-correlation of each trace with the stack of the section of the previous iteration. The iteration yielding the section with the highest degree of lateral coherency (semblance) is used to extract the travel-time pick of each trace. The pick, plus a possible d.c. component, is the negative of the time shift required to achieve arrival alignment. Two modifications can improve the performance of the picking routine. To prevent a cycle skipping problem, a Monte Carlo technique is implemented in which the cross-correlation function is transformed into a probability distribution so that the lag corresponding to the maximum cross-correlation is most probably selected. Second, to increase the coherency of the arrivals, a spectral balancing technique is applied in either the time or frequency domain. The picking routine is applied to both a synthetic and real data example, and the results suggest that the routine can be applied successfully to data with a signal-to-noise ratio as low as one. Also, the Monte Carlo procedure together with spectral balancing increases the final semblance over that obtained with the unmodified method.

The Influence of Alteration of kVp and mAs towards the Image Quality of Acrylic Using CBCT

2019 ◽  
Vol 829 ◽  
pp. 252-257
Author(s):  
Azhari ◽  
Yohanes Hutasoit ◽  
Freddy Haryanto
Keyword(s):  
Image Quality ◽  
Signal To Noise Ratio ◽  
Region Of Interest ◽  
Signal To Noise ◽  
Bite Block ◽  
Significant Difference ◽  
Noise Ratio ◽  
Post Hoc ◽  
Radiograph Image

CBCT is a modernized technology in producing radiograph image on dentistry. The image quality excellence is very important for clinicians to interpret the image, so the result of diagnosis produced becoming more accurate, appropriate, thus minimizing the working time. This research was aimed to assess the image quality using the blank acrylic phantom polymethylmethacrylate (PMMA) (C­5H8O2)n in the density of 1.185 g/cm3 for evaluating the homogeneity and uniformity of the image produced. Acrylic phantom was supported with a tripod and laid down on the chin rest of the CBCT device, then the phantom was fixed, and the edge of the phantom was touched by the bite block. Furthermore, the exposure of the X-ray was executed toward the acrylic phantom with various kVp and mAs, from 80 until 90, with the range of 5 kV and the variation of mA was 3, 5, and 7 mA respectively. The time exposure was kept constant for 25 seconds. The samples were taken from CBCT acrylic images, then as much as 5 ROIs (Region of Interest) was chosen to be analyzed. The ROIs determination was analyzed by using the ImageJ® software for recognizing the influence of kVp and mAs towards the image uniformity, noise and SNR. The lowest kVp and mAs had the result of uniformity value, homogeneity and signal to noise ratio of 11.22; 40.35; and 5.96 respectively. Meanwhile, the highest kVp and mAs had uniformity value, homogeneity and signal to noise ratio of 16.96; 26.20; and 5.95 respectively. There were significant differences between the image uniformity and homogeneity on the lowest kVp and mAs compared to the highest kVp and mAs, as analyzed with the ANOVA statistics analysis continued with the t-student post-hoc test with α = 0.05. However, there was no significant difference in SNR as analyzed with the ANOVA statistic analysis. The usage of the higher kVp and mAs caused the improvement of the image homogeneity and uniformity compared to the lower kVp and mAs.

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