scholarly journals An Adaptive Image Inpainting Method Based on Continued Fractions Interpolation

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Lei He ◽  
Yan Xing ◽  
Kangxiong Xia ◽  
Jieqing Tan
Keyword(s):  
Continued Fractions ◽  
State Of The Art ◽  
Signal To Noise Ratio ◽  
Subjective Evaluation ◽  
Image Inpainting ◽  
Rational Interpolation ◽  
Objective Evaluation ◽  
Experimental Results ◽  
Signal To Noise

In view of the drawback of most image inpainting algorithms by which texture was not prominent, an adaptive inpainting algorithm based on continued fractions was proposed in this paper. In order to restore every damaged point, the information of known pixel points around the damaged point was used to interpolate the intensity of the damaged point. The proposed method included two steps; firstly, Thiele’s rational interpolation combined with the mask image was used to interpolate adaptively the intensities of damaged points to get an initial repaired image, and then Newton-Thiele’s rational interpolation was used to refine the initial repaired image to get a final result. In order to show the superiority of the proposed algorithm, plenty of experiments were tested on damaged images. Subjective evaluation and objective evaluation were used to evaluate the quality of repaired images, and the objective evaluation was comparison of Peak Signal to Noise Ratios (PSNRs). The experimental results showed that the proposed algorithm had better visual effect and higher Peak Signal to Noise Ratio compared with the state-of-the-art methods.

An Effective LFM Signal Reconstruction Method for Signal Denoising

2018 ◽  
Vol 27 (09) ◽  
pp. 1850140
Author(s):  
Shan Luo ◽  
Guoan Bi ◽  
Tong Wu ◽  
Yong Xiao ◽  
Rongping Lin
Keyword(s):  
Signal To Noise Ratio ◽  
Signal Reconstruction ◽  
Experimental Results ◽  
Signal Denoising ◽  
Reconstruction Method ◽  
Signal To Noise ◽  
Time Frequency ◽  
Effective Time ◽  
Reconstructed Signal

One of the main challenges in signal denoising is to accurately restore useful signals in low signal-to-noise ratio (SNR) scenarios. In this paper, we investigate the signal denoising problem for multi-component linear frequency modulated (LFM) signals. An effective time-frequency (TF) analysis-based approach is proposed. Compared to the existing approaches, our proposed one can further increase the noise suppressing performance and improve the quality of the reconstructed signal. Experimental results are presented to show that the proposed denoising approach is able to effectively separate the multi-component LFM signal from the strong noise environments.

Research of Leak Detection and Location Method for Heat Oil Pipelines

2008 ◽  
Author(s):  
Laibin Zhang ◽  
Zhigang Chen ◽  
Wei Liang ◽  
Mingda Wang
Keyword(s):  
Pressure Wave ◽  
Integration Method ◽  
Signal To Noise Ratio ◽  
Temperature Drop ◽  
Experimental Results ◽  
Signal To Noise ◽  
Axial Temperature ◽  
Oil Pipelines ◽  
Novel Method

It is an effective method to detect leak using negative pressure wave (NPW). When heat oil pipelines in low transfer throughput and complex operational changes, usually noise will be very strong and feature signal of leak is difficult to extract. In order to improve quality of parameter information collected, a novel method based on Independent Component Analysis (ICA) is proposed to separate and filter weak aim signal from noise. In this paper signal processing principle based ICA is introduced and experiments are illustrated. The experimental results show that signal-to-noise ratio (SNR) of processed pressure signals is raised effectively and feature signal become easy to extract. At the same time, in heat oil pipelines pressure wave velocity is affected by oil and axial temperature drop. Location usually has obvious error. To solve this problem axial temperature drop is analyzed and velocity of NPW was revised. By means of Newton-Cotes integration method location formula is modified. The real experimental results show that the improved located formula made location accuracy from 2.5% to 1.0%.

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

METHODOLOGY OF OBJECTIVE EVALUATION OF THE QUALITY BEARINGS BY VIBRO-ACOUSTICS AND ITS COMPARISON WITH A SUBJECTIVE METHOD

Akustika ◽  
2020 ◽  
pp. 58-66
Author(s):  
Stanislav Žiaran ◽  
Ondrej Chlebo ◽  
Ĺubomír Šooš
Keyword(s):  
Dynamic Load ◽  
Subjective Evaluation ◽  
Objective Evaluation ◽  
Living Environment ◽  
Working Environment ◽  
Subjective Method ◽  
Auditory Organ ◽  
Objective Methodology ◽  
Fft Analysis

The quality of bearing production has an impact not only on their reliability and lifetime, but also on the dynamic load of the working and living environment by excessive vibration and thus also noise. The intensity of the noise emitted by a bearing which is perceived by man characterizes the quality of its production. Reducing the dynamic load of mechanical systems and their components is reflected in the working environment by reducing noise emissions and immissions. The article proposes an objective method of bearing quality assessment based on measuring vibro-acoustic parameters of dynamic load of a new bearing using FFT analysis and the magnitude of the amplitude of bearing vibration acceleration and compares it with a subjective method that also uses the human auditory organ to assess bearing quality. The results of vibro-acoustic measurements were analysed in terms of vibration intensity and the noise of the produced bearings. The proposed objective methodology was compared with the subjective evaluation of the quality of bearings and the results of this methodology matched. The proposed methodology is applicable to all types of bearings, and it is possible to automate this methodology in the production process.

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.

scholarly journals Contour Detection for Fibre of Preserved Szechuan Pickle Based on Dilated Convolution

2019 ◽  
Vol 9 (13) ◽  
pp. 2684 ◽  
Author(s):  
Hongyang Li ◽  
Lizhuang Liu ◽  
Zhenqi Han ◽  
Dan Zhao
Keyword(s):  
Edge Detection ◽  
State Of The Art ◽  
Contour Detection ◽  
Experimental Results ◽  
Contour Method ◽  
Class Differences ◽  
Dilated Convolution ◽  
The Mean ◽  
Art Performance

Peeling fibre is an indispensable process in the production of preserved Szechuan pickle, the accuracy of which can significantly influence the quality of the products, and thus the contour method of fibre detection, as a core algorithm of the automatic peeling device, is studied. The fibre contour is a kind of non-salient contour, characterized by big intra-class differences and small inter-class differences, meaning that the feature of the contour is not discriminative. The method called dilated-holistically-nested edge detection (Dilated-HED) is proposed to detect the fibre contour, which is built based on the HED network and dilated convolution. The experimental results for our dataset show that the Pixel Accuracy (PA) is 99.52% and the Mean Intersection over Union (MIoU) is 49.99%, achieving state-of-the-art performance.

Multilag Correlation Estimators for Polarimetric Radar Measurements in the Presence of Noise

2012 ◽  
Vol 29 (6) ◽  
pp. 772-795 ◽  
Author(s):  
Lei Lei ◽  
Guifu Zhang ◽  
Richard J. Doviak ◽  
Robert Palmer ◽  
Boon Leng Cheong ◽  
...  
Keyword(s):  
Theoretical Analysis ◽  
Data Quality ◽  
Signal To Noise Ratio ◽  
Simulated Data ◽  
Radar Data ◽  
Polarimetric Radar ◽  
Signal To Noise ◽  
Spectral Moments ◽  
Radar Measurements

Abstract The quality of polarimetric radar data degrades as the signal-to-noise ratio (SNR) decreases. This substantially limits the usage of collected polarimetric radar data to high SNR regions. To improve data quality at low SNRs, multilag correlation estimators are introduced. The performance of the multilag estimators for spectral moments and polarimetric parameters is examined through a theoretical analysis and by the use of simulated data. The biases and standard deviations of the estimates are calculated and compared with those estimates obtained using the conventional method.

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.

scholarly journals Implementation of Spatial-Scale Domain Based De-Noising Techniques using Different Thresholding

2020 ◽  
Vol 9 (3) ◽  
pp. 3594-3603
Keyword(s):  
Wavelet Transform ◽  
Root Mean Square Error ◽  
Signal To Noise Ratio ◽  
Objective Evaluation ◽  
Contourlet Transform ◽  
Discrete Wavelet ◽  
Mean Square ◽  
Stationary Wavelet Transform ◽  
Signal To Noise ◽  
Different Levels

This paper aims in presenting a thorough comparison of performance and usefulness of multi-resolution based de-noising technique. Multi-resolution based image denoising techniques overcome the limitation of Fourier, spatial, as well as, purely frequency based techniques, as it provides the information of 2-Dimensional (2-D) signal at different levels and scales, which is desirable for image de-noising. The multiresolution based de-noising techniques, namely, Contourlet Transform (CT), Non Sub-sampled Contourlet Transform (NSCT), Stationary Wavelet Transform (SWT) and Discrete Wavelet Transform (DWT), have been selected for the de-noising of camera images. Further, the performance of different denosing techniques have been compared in terms of different noise variances, thresholding techniques and by using well defined metrics, such as Peak Signal-to-Noise Ratio (PSNR) and Root Mean Square Error (RMSE). Analysis of result shows that shift-invariant NSCT technique outperforms the CT, SWT and DWT based de-noising techniques in terms of qualititaive and quantitative objective evaluation

scholarly journals Discovery of allenyl acetylene, H2CCCHCCH, in TMC-1

2021 ◽  
Vol 647 ◽  
pp. L3 ◽  
Author(s):  
J. Cernicharo ◽  
C. Cabezas ◽  
M. Agúndez ◽  
B. Tercero ◽  
N. Marcelino ◽  
...  
Keyword(s):  
Column Density ◽  
State Of The Art ◽  
Rotational Temperature ◽  
Signal To Noise Ratio ◽  
Laboratory Data ◽  
The Other ◽  
Signal To Noise ◽  
Chemical Models ◽  
Upper Limit

We present the discovery in TMC-1 of allenyl acetylene, H2CCCHCCH, through the observation of nineteen lines with a signal-to-noise ratio ∼4–15. For this species, we derived a rotational temperature of 7 ± 1 K and a column density of 1.2 ± 0.2 × 1013 cm−2. The other well known isomer of this molecule, methyl diacetylene (CH3C4H), has also been observed and we derived a similar rotational temperature, Tr = 7.0 ± 0.3 K, and a column density for its two states (A and E) of 6.5 ± 0.3 × 1012 cm−2. Hence, allenyl acetylene and methyl diacetylene have a similar abundance. Remarkably, their abundances are close to that of vinyl acetylene (CH2CHCCH). We also searched for the other isomer of C5H4, HCCCH2CCH (1.4-Pentadiyne), but only a 3σ upper limit of 2.5 × 1012 cm−2 to the column density can be established. These results have been compared to state-of-the-art chemical models for TMC-1, indicating the important role of these hydrocarbons in its chemistry. The rotational parameters of allenyl acetylene have been improved by fitting the existing laboratory data together with the frequencies of the transitions observed in TMC-1.

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