Contrast Enhancement Method Based on Gray and Its Distance Double-Weighting Histogram Equalization for 3D CT Images of PCBs

Cone beam computed tomography (CBCT) is a new detection method for 3D nondestructive testing of printed circuit boards (PCBs). However, the obtained 3D image of PCBs exhibits low contrast because of several factors, such as the occurrence of metal artifacts and beam hardening, during the process of CBCT imaging. Histogram equalization (HE) algorithms cannot effectively extend the gray difference between a substrate and a metal in 3D CT images of PCBs, and the reinforcing effects are insignificant. To address this shortcoming, this study proposes an image enhancement algorithm based on gray and its distance double-weighting HE. Considering the characteristics of 3D CT images of PCBs, the proposed algorithm uses gray and its distance double-weighting strategy to change the form of the original image histogram distribution, suppresses the grayscale of a nonmetallic substrate, and expands the grayscale of wires and other metals. The proposed algorithm also enhances the gray difference between a substrate and a metal and highlights metallic materials. The proposed algorithm can enhance the gray value of wires and other metals in 3D CT images of PCBs. It applies enhancement strategies of changing gray and its distance double-weighting mechanism to adapt to this particular purpose. The flexibility and advantages of the proposed algorithm are confirmed by analyses and experimental results.

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An Image Enhancement Method Based on the Coal Mine Monitoring System

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.468-471.204 ◽

2012 ◽

Vol 468-471 ◽

pp. 204-207

Author(s):

Zhen Chong Wang ◽

Yan Qin Zhao

Keyword(s):

Image Enhancement ◽

Coal Mine ◽

Impulse Noise ◽

Histogram Equalization ◽

Video Monitor ◽

Low Contrast ◽

Adaptive Histogram Equalization ◽

Enhancement Method ◽

Special Environment

For the low illumination and low contrast in the coal mine, images captured from the video monitor system sometimes are not so clear to help the related personal monitoring the production and safety of the mine. According to the special environment of coal mine, an image enhancement method was presented. In this method the impulse noise which is the mainly noise in the coal mine was first reduced with median filtering, then the low contrast and illumination was greatly improved with the improved adaptive histogram equalization. Experiments show that this method can improve the quality of images underground effectively.

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An image enhancement method based on gabor filtering in wavelet domain and adaptive histogram equalization

Indonesian Journal of Electrical Engineering and Computer Science ◽

10.11591/ijeecs.v21.i1.pp146-153 ◽

2021 ◽

Vol 21 (1) ◽

pp. 146

Author(s):

Jeevan K M ◽

Anne Gowda A B ◽

Padmaja Vijay Kumar

Keyword(s):

Image Enhancement ◽

Histogram Equalization ◽

Median Filtering ◽

Wavelet Domain ◽

Gabor Filtering ◽

Low Contrast ◽

Enhancement Technique ◽

Adaptive Histogram Equalization ◽

Enhancement Method ◽

Two Parameters

<p><span>The images are not always good enough to convey the proper information. The image may be very bright or very dark sometime or it may be low contrast or high contrast. Because of these reasons image enhancement plays important role in digital image processing. In this paper we proposed an image enhancement technique in which Gabor and median filtering is performed in wavelet domain and Adaptive Histogram Equalization is performed in spatial domain. Brightness and contrast are the two parameters used for analyzing the performance of the proposed method</span></p>

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A POSHE-Based Optimum Clip-Limit Contrast Enhancement Method for Ultrasonic Logging Images

Sensors ◽

10.3390/s18113954 ◽

2018 ◽

Vol 18 (11) ◽

pp. 3954 ◽

Cited By ~ 1

Author(s):

Qingqing Fu ◽

Zhengbing Zhang ◽

Mehmet Celenk ◽

Aiping Wu

Keyword(s):

Contrast Enhancement ◽

Structural Similarity ◽

Histogram Equalization ◽

Input Image ◽

Distribution Functions ◽

Cumulative Distribution ◽

Low Contrast ◽

Perceptual Evaluation ◽

Limit Value ◽

Enhancement Method

Enabled by piezoceramic transducers, ultrasonic logging images often suffer from low contrast and indistinct local details, which makes it difficult to analyze and interpret geologic features in the images. In this work, we propose a novel partially overlapped sub-block histogram-equalization (POSHE)-based optimum clip-limit contrast enhancement (POSHEOC) method to highlight the local details hidden in ultrasonic well logging images obtained through piezoceramic transducers. The proposed algorithm introduces the idea of contrast-limited enhancement to modify the cumulative distribution functions of the POSHE and build a new quality evaluation index considering the effects of the mean gradient and mean structural similarity. The new index is designed to obtain the optimal clip-limit value for histogram equalization of the sub-block. It makes the choice of the optimal clip-limit automatically according to the input image. Experimental results based on visual perceptual evaluation and quantitative measures demonstrate that the proposed method yields better quality in terms of enhancing the contrast, emphasizing the local details while preserving the brightness and restricting the excessive enhancement compared with the other seven histogram equalization-based techniques from the literature. This study provides a feasible and effective method to enhance ultrasonic logging images obtained through piezoceramic transducers and is significant for the interpretation of actual ultrasonic logging data.

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

Mathematical Problems in Engineering ◽

10.1155/2020/7095248 ◽

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.

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Research on Enhanced of Mine-Underground Picture

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.490-495.548 ◽

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.

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Contrast Enhancement of Mammograms and Microcalcification Detection

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.f2473.118419 ◽

2019 ◽

Vol 8 (4) ◽

pp. 3926-3932

Keyword(s):

Operative Procedure ◽

Histogram Equalization ◽

Local Contrast ◽

Edge Information ◽

Edge Structure ◽

Low Contrast ◽

Structure Information ◽

Enhancement Method ◽

Microcalcification Detection ◽

Mammogram Images

Mammography is an operative procedure for early detection of cancer present in breast. However, the pathological changes of the breast are difficult to interpret from low contrast mammograms. This research proposes a method to enhance the contrast of the mammogram that uses Non-subsampled contourlet transform (NSCT) based edge information. Instead of a directional filter bank in the conventional NSCT structure, this paper uses multiscale non-separable edge filters. These edge filters outputs intrinsic edge structure information based on simplified hyperbolic tangent function applied with two polarized schemes. This edge information further used to improve the local contrast. Adaptive histogram equalization (AHE) also used to increase the overall contrast of mammogram. Improved detection of microcalcification (MC) from enhanced mammogram images shows the success of this algorithm. This method has better enhancement measure (EME) than AHE and unsharp based mammogram enhancement method.

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