scholarly journals Image Enhancement for Inspection of Cable Images Based on Retinex Theory and Fuzzy Enhancement Method in Wavelet Domain

Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 570 ◽  
Author(s):  
Xuhui Ye ◽  
Gongping Wu ◽  
Le Huang ◽  
Fei Fan ◽  
Yongxiang Zhang
Keyword(s):  
Image Quality ◽  
Power Transmission ◽  
Low Frequency ◽  
Speckle Noise ◽  
Standard Test ◽  
Low Contrast ◽  
Inspection Robot ◽  
Fuzzy Enhancement ◽  
Enhancement Method ◽  
Frequency Components

Inspection images of power transmission line provide vision interaction for the operator and the environmental perception for the cable inspection robot (CIR). However, inspection images are always contaminated by severe outdoor working conditions such as uneven illumination, low contrast, and speckle noise. Therefore, this paper proposes a novel method based on Retinex and fuzzy enhancement to improve the image quality of the inspection images. A modified multi-scale Retinex (MSR) is proposed to compensate the uneven illumination by processing the low frequency components after wavelet decomposition. Besides, a fuzzy enhancement method is proposed to perfect the edge information and improve contrast by processing the high frequency components. A noise reduction procedure based on soft threshold is used to avoid the noise amplification. Experiments on the self-built standard test dataset show that the algorithm can improve the image quality by 3–4 times. Compared with several other methods, the experimental results demonstrate that the proposed method can obtain better enhancement performance with more homogeneous illumination and higher contrast. Further research will focus on improving the real-time performance and parameter adaptation of the algorithm.

Underwater Image Enhancement Method Combining color and Luminance

2020 ◽  
Vol 13 ◽  
Author(s):  
ZHAO Baiting ◽  
WANG Feng ◽  
JIA Xiaofen ◽  
GUO Yongcun ◽  
WANG Chengjun
Keyword(s):  
Image Enhancement ◽  
Color Space ◽  
Low Frequency ◽  
Brightness Enhancement ◽  
Color Distortion ◽  
Underwater Image ◽  
Enhancement Method ◽  
Frequency Components ◽  
Image Contour ◽  
Objective Indicators

Background:: Aiming at the problems of color distortion, low clarity and poor visibility of underwater image caused by complex underwater environment, a wavelet fusion method UIPWF for underwater image enhancement is proposed. Methods:: First of all, an improved NCB color balance method is designed to identify and cut the abnormal pixels, and balance the color of R, G and B channels by affine transformation. Then, the color correction map is converted to CIELab color space, and the L component is equalized with contrast limited adaptive histogram to obtain the brightness enhancement map. Finally, different fusion rules are designed for low-frequency and high-frequency components, the pixel level wavelet fusion of color balance image and brightness enhancement image is realized to improve the edge detail contrast on the basis of protecting the underwater image contour. Results:: The experiments demonstrate that compared with the existing underwater image processing methods, UIPWF is highly effective in the underwater image enhancement task, improves the objective indicators greatly, and produces visually pleasing enhancement images with clear edges and reasonable color information. Conclusion:: The UIPWF method can effectively mitigate the color distortion, improve the clarity and contrast, which is applicable for underwater image enhancement in different environments.

scholarly journals Seismic section image detail enhancement method based on bilateral texture filtering and adaptive enhancement of texture details

2020 ◽  
Vol 27 (2) ◽  
pp. 253-260
Author(s):  
Xiang-Yu Jia ◽  
Chang-Lei DongYe
Keyword(s):  
High Frequency ◽  
Structural Information ◽  
Low Frequency ◽  
Frequency Noise ◽  
Seismic Section ◽  
Multi Scale ◽  
Adaptive Enhancement ◽  
Enhancement Method ◽  
Frequency Components ◽  
Texture Filtering

Abstract. The seismic section image contains a wealth of texture detail information, which is important for the interpretation of the formation profile information. In order to enhance the texture detail of the image while keeping the structural information of the image intact, a multi-scale enhancement method based on wavelet transform is proposed. Firstly, the image is wavelet decomposed to obtain a low-frequency structural component and a series of high-frequency texture detail components. Secondly, bilateral texture filtering is performed on the low-frequency structural components to filter out high-frequency noise while maintaining the edges of the image; adaptive enhancement is performed on the high-frequency detail components to filter out low-frequency noise while enhancing detail. Finally, the processed high- and low-frequency components reconstructed by wavelets can obtain a seismic section image with enhanced detail. The method of this paper enhances the texture detail information in the image while preserving the edge of the image.

scholarly journals Denoising Method for Passive Photon Counting Images Based on Block-Matching 3D Filter and Non-Subsampled Contourlet Transform

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2462
Author(s):  
Xuan Wang ◽  
Liju Yin ◽  
Mingliang Gao ◽  
Zhenzhou Wang ◽  
Jin Shen ◽  
...  
Keyword(s):  
High Frequency ◽  
Photon Counting ◽  
Low Frequency ◽  
Operation Time ◽  
Objective Evaluation ◽  
Block Matching ◽  
Contourlet Transform ◽  
Denoising Method ◽  
Low Contrast ◽  
Enhancement Method

Multi-pixel photon counting detectors can produce images in low-light environments based on passive photon counting technology. However, the resulting images suffer from problems such as low contrast, low brightness, and some unknown noise distribution. To achieve a better visual effect, this paper describes a denoising and enhancement method based on a block-matching 3D filter and a non-subsampled contourlet transform (NSCT). First, the NSCT was applied to the original image and histogram-equalized image to obtain the sub-band low- and high-frequency coefficients. Regional energy and scale correlation rules were used to determine the respective coefficients. Adaptive single-scale retinex enhancement was applied to the low-frequency components to improve the image quality. The high-frequency sub-bands whose line features were best preserved were selected and processed using a symbol function and the Bayes-shrink threshold. After applying the inverse transform, the fused photon counting image was subjected to an improved block-matching 3D filter, significantly reducing the operation time. The final result from the proposed method was superior to those of comparative methods in terms of several objective evaluation indices and exhibited good visual effects and details from the objective impression.

scholarly journals Multiscale Fusion Method for the Enhancement of Low-Light Underwater Images

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Jingchun Zhou ◽  
Dehuan Zhang ◽  
Weishi Zhang
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Histogram Equalization ◽  
Gradient Field ◽  
Low Contrast ◽  
Frequency Information ◽  
Underwater Image ◽  
Enhancement Method ◽  
Quantitative Performance ◽  
Color Cast

To solve the color cast and low contrast of underwater images caused by the effects of light absorption and scattering, we propose a novel underwater image enhancement method via bi-interval histogram equalization. The proposed method consists of three main parts: color correction, contrast enhancement, and multiscale fusion. First, the color cast is eliminated by automatic white balancing. Then, homomorphic filtering is adopted to decompose the image into high-frequency information and low-frequency information, the high-frequency information is enhanced by the gradient field bi-interval equalization which enhances the contrast and details of the image, and the low-frequency information is disposed via gamma correction for adjusting the exposure. Finally, we adopt a multiscale fusion strategy to fuse the high-frequency information, high-frequency after bi-interval equalization, and low-frequency information based on contrast, saturation, and exposure. Qualitative and quantitative performance evaluations demonstrate that the proposed method can effectively enhance the details and global contrast of the image and achieve better exposedness of the dark areas, which outperforms several state-of-the-art methods.

scholarly journals CALCULATION OF POWER LINE FIELDS BETWEEN CIRCULAR CONDUCTORS

2012 ◽  
Vol 04 (01) ◽  
pp. 1250025
Author(s):  
ANDREW SEAGAR ◽  
SALAKCHIT NILBOWORN
Keyword(s):  
Electric Field ◽  
Transmission Lines ◽  
Power Transmission ◽  
Circular Cross Section ◽  
Low Frequency ◽  
Test Cases ◽  
Power Transmission Lines ◽  
System Matrix ◽  
High Voltage Direct Current ◽  
Frequency Components

It is important to calculate the electric field at the surface of high voltage direct current power transmission lines, since it is this field which governs the onset of corona discharge and the power loss arising therefrom. A method is presented here to calculate the electric field based on an implementation of the boundary element method for conductors of strictly circular cross section. Given the circular geometry it is possible to resolve all integrals involved analytically. A Galerkin approach is adopted, giving the solution in the spatial frequency domain. That allows a controlled truncation of the system matrix by choice of which frequency components to keep. It transpires that the low frequency components are the most important ones. Two test cases are used to quantify the accuracy of the solution with respect to truncation and distance from the surface. It is found that the accuracy increases with distance from the surface, but for all distances can be controlled by choosing an appropriate level of truncation.

Research on Enhanced of Mine-Underground Picture

2012 ◽  
Vol 490-495 ◽  
pp. 548-552
Author(s):  
Meng Ling Zhao ◽  
Min Xia Jiang
Keyword(s):  
Image Quality ◽  
Signal To Noise Ratio ◽  
Ccd Camera ◽  
Histogram Equalization ◽  
Uniform Illumination ◽  
Improve Image Quality ◽  
Low Contrast ◽  
Enhancement Method ◽  
Field Information ◽  
Time Image

Because of the based on S3C6410 Field information recorder mine- underground non-uniform illumination and mine- underground non-uniform illumination that a large of noise collected and transferred,image is low contrast ,dim and dark. Based on the theory of Donoho's wavelet threshold denoising, several typical wavelet threshold denoising methods are compared.the best denoising effect of peak signal to noise ratio is obtained. The image enhancement method that combination of the adaptive thresholding denoising and histogram equalization is proposed. The experiment result shows that the method has a good denoising performance, which removed the readout noise of CCD Camera,at the same time, image quality is improved .So the wavelet enhancement in image processing of mine- underground can improve image quality.

scholarly journals Seismic section image detail enhancement method based on wavelet transform

2019 ◽  
Author(s):  
Xiang-Yu Jia ◽  
Chang-Lei DongYe
Keyword(s):  
Wavelet Transform ◽  
High Frequency ◽  
Structural Information ◽  
Low Frequency ◽  
Frequency Noise ◽  
Seismic Section ◽  
Adaptive Enhancement ◽  
Enhancement Method ◽  
Frequency Components ◽  
Texture Filtering

Abstract. The seismic section image contains a wealth of texture detail information, which is important for the interpretation of the formation profile information. In order to enhance the texture detail of the image while keeping the structural information of the image intact, a multi-scale enhancement method based on wavelet transform is proposed. First, the image is wavelet decomposed to obtain a low frequency structural component and a series of high frequency texture detail components; Secondly, bilateral texture filtering is performed on the low-frequency structural components to filter out high-frequency noise while maintaining the edges of the image; adaptive enhancement is performed on the high-frequency detail components to filter out low-frequency noise while enhancing detail; Finally, the processed high and low frequency components are reconstructed by wavelet can obtained the seismic section image with enhanced detail. The method of this paper enhances the texture detail information in the image while preserving the edge of the image.

An Ultrasound Image Enhancement Method Using Neutrosophic Similarity Score

2020 ◽  
Vol 42 (6) ◽  
pp. 271-283
Author(s):  
Puja Bharti ◽  
Deepti Mittal
Keyword(s):  
Image Quality ◽  
Image Quality Assessment ◽  
Subjective Evaluation ◽  
Similarity Score ◽  
Input Image ◽  
Ultrasound Images ◽  
Edge Preservation ◽  
Low Contrast ◽  
Interactive Decision Making ◽  
Enhancement Method

Ultrasound images, having low contrast and noise, adversely impact in the detection of abnormalities. In view of this, an enhancement method is proposed in this work to reduce noise and improve contrast of ultrasound images. The proposed method is based on scaling with neutrosophic similarity score (NSS), where an image is represented in the neutrosophic domain through three membership subsets T, I, and F denoting the degree of truth, indeterminacy, and falseness, respectively. The NSS measures the belonging degree of pixel to the texture using multi-criteria that is based on intensity, local mean intensity and edge detection. Then, NSS is utilized to extract the enhanced coefficient and this enhanced coefficient is applied to scale the input image. This scaling reflects contrast improvement and denoising effect on ultrasound images. The performance of proposed enhancement method is evaluated on clinical ultrasound images, using both subjective and objective image quality measures. In subjective evaluation, with proposed method, overall best score of 4.3 was obtained and that was 44% higher than the score of original images. These results were also supported by objective measures. The results demonstrated that the proposed method outperformed the other methods in terms of mean brightness preservation, edge preservation, structural similarity, and human perception-based image quality assessment. Thus, the proposed method can be used in computer-aided diagnosis systems and to visually assist radiologists in their interactive-decision-making task.

scholarly journals Image Deconvolution with Hybrid Reweighted Adaptive Total Variation (HRATV) for Optoacoustic Tomography

Photonics ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 25
Author(s):  
Chen Yang ◽  
Yang Jiao ◽  
Xiaohua Jian ◽  
Yaoyao Cui
Keyword(s):  
Image Quality ◽  
Total Variation ◽  
Imaging Modality ◽  
Standard Test ◽  
Image Deconvolution ◽  
Low Contrast ◽  
Limited Bandwidth ◽  
Optoacoustic Tomography ◽  
Adaptive Total Variation

Optoacoustic tomography (OAT) is a hybrid biomedical imaging modality that usually employs a transducer array to detect laser-generated ultrasonic signals. The reconstructed image suffers low contrast and degraded resolution due to the limited bandwidth and the spatial directivity of the transducer element. Here, we introduce a modified image deconvolution method with a hybrid reweighted adaptive total variation tailored to improve the image quality of OAT. The effectiveness and the parameter dependency of the proposed method are verified on standard test images. The performance of the proposed method in OAT is then characterized on both simulated phantoms and in vivo mice experiments, which demonstrates that the modified deconvolution algorithm is able to restore the sharp edges and fine details in OAT simultaneously. The signal-to-noise ratios (SNRs) of the target structures in mouse liver and brain were improved by 4.90 and 12.69 dB, respectively. We also investigated the feasibility of using Fourier ring correlation (FRC) as an indicator of the image quality to monitor the deconvolution progress in OAT. Based on the experimental results, a practical guide for image deconvolution in OAT was summarized. We anticipate that the proposed method will be a promising post-processing tool to enhance the visualization of micro-structures in OAT.

Simulations of high-resolution images of amorphous silicon films

1986 ◽  
Vol 44 ◽  
pp. 544-545
Author(s):  
G. Y. Fan ◽  
J. M. Cowley
Keyword(s):  
Electron Microscope ◽  
High Frequency ◽  
Fourier Transformation ◽  
Amorphous Materials ◽  
Low Frequency ◽  
Chromatic Aberration ◽  
Structure Information ◽  
Frequency Components ◽  
High Resolution Images ◽  
Spatial Frequency Spectrum

It is well known that the structure information on the specimen is not always faithfully transferred through the electron microscope. Firstly, the spatial frequency spectrum is modulated by the transfer function (TF) at the focal plane. Secondly, the spectrum suffers high frequency cut-off by the aperture (or effectively damping terms such as chromatic aberration). While these do not have essential effect on imaging crystal periodicity as long as the low order Bragg spots are inside the aperture, although the contrast may be reversed, they may change the appearance of images of amorphous materials completely. Because the spectrum of amorphous materials is continuous, modulation of it emphasizes some components while weakening others. Especially the cut-off of high frequency components, which contribute to amorphous image just as strongly as low frequency components can have a fundamental effect. This can be illustrated through computer simulation. Imaging of a whitenoise object with an electron microscope without TF limitation gives Fig. 1a, which is obtained by Fourier transformation of a constant amplitude combined with random phases generated by computer.

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