scholarly journals Correction of Color Cast Images using Histogram Equalization of Local Area

2016 ◽  
Author(s):  
Makoto Misumi ◽  
Hideaki Orii ◽  
Tanjina Sharmin ◽  
Kenji Mishima
Keyword(s):  
Local Area ◽  
Histogram Equalization ◽  
Color Cast

Fabric defect detection based on a deep convolutional neural network using a two-stage strategy

2020 ◽  
Vol 91 (1-2) ◽  
pp. 130-142 ◽  
Author(s):  
Xiang Jun ◽  
Jingan Wang ◽  
Jian Zhou ◽  
Shuo Meng ◽  
Ruru Pan ◽  
...  
Keyword(s):  
Defect Detection ◽  
Textile Industry ◽  
Local Area ◽  
Histogram Equalization ◽  
Research Field ◽  
Superior Performance ◽  
Local Defect ◽  
Labor Costs ◽  
Fabric Defect Detection ◽  
Fabric Defect

With the rise of labor costs and the advancement of automation in the textile industry, fabric defect detection has become a hot research field in recent years. We proposed a learning-based framework for automatic detection of fabric defects. Firstly, we use a fixed-size square slider to crop the original image to a certain step and regularity. Then an improved histogram equalization is used to enhance each cropped image. Furthermore, the Inception-V1 model is employed to predict the existence of defects in the local area. Finally, we apply the LeNet-5 model, which plays the role of a voting model, to recognize the type of the defect in the fabric. In brief, the proposed framework mainly consists of two steps, namely local defect prediction and global defect recognition. Experiments on the dataset have demonstrated the superior performance in fabric defect detection.

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.

Contrast Limited Adaptive Histogram Equalization-Based Fusion in YIQ and HSI Color Spaces for Underwater Image Enhancement

2018 ◽  
Vol 32 (07) ◽  
pp. 1854018 ◽  
Author(s):  
Jinxiang Ma ◽  
Xinnan Fan ◽  
Simon X. Yang ◽  
Xuewu Zhang ◽  
Xifang Zhu
Keyword(s):  
Image Enhancement ◽  
Color Image ◽  
Histogram Equalization ◽  
Color Spaces ◽  
Fusion Algorithm ◽  
Noise Interference ◽  
Adaptive Histogram Equalization ◽  
Rgb Images ◽  
Color Cast ◽  
Three Components

To improve contrast and restore color for underwater images without suffering from insufficient details and color cast, this paper proposes a fusion algorithm for different color spaces based on contrast limited adaptive histogram equalization (CLAHE). The original color image is first converted from RGB space to two different spaces: YIQ and HSI. Then, the algorithm separately applies CLAHE in YIQ and HSI color spaces to obtain two different enhanced images. After that, the YIQ and HSI enhanced images are respectively converted back to RGB space. When the three components of red, green, and blue are not coherent in the YIQ-RGB or HSI-RGB images, the three components will have to be harmonized with the CLAHE algorithm in RGB space. Finally, using a 4-direction Sobel edge detector in the bounded general logarithm ratio operation, a self-adaptive weight selection nonlinear image enhancement is carried out to fuse the YIQ-RGB and HSI-RGB images together to achieve the final image. The experimental results showed that the proposed algorithm provided more detail enhancement and higher values of color restoration than other image enhancement algorithms. The proposed algorithm can effectively reduce noise interference and observably improve the image quality for underwater images.

Adaptive Stretching Method for Underwater Image Color Correction

2017 ◽  
Vol 32 (02) ◽  
pp. 1854001 ◽  
Author(s):  
Jun Ao ◽  
Chunbo Ma
Keyword(s):  
Performance Analysis ◽  
Water Channel ◽  
Computational Cost ◽  
Histogram Equalization ◽  
Subjective Impression ◽  
Low Contrast ◽  
Underwater Image ◽  
Color Spectrum ◽  
Color Cast ◽  
Image Performance

The physical properties of water lead to attenuation of light that travels through the water channel. The attenuation is dependent on the color spectrum wavelength, that results in low contrast and color cast in image acquisition. Several methods have been proposed to handle these problems, such as Linear Stretching, Histogram Equalization (HE) and their variants. Considering the advantages of HE and Linear Stretching, this paper presents a new Adaptive Linear Stretch method (ALS) which can efficiently improve the subjective impression of the traditional Linear Stretching and keep the computational cost low at the same time. To achieve adaptability, the adaptable threshold is deduced from the histogram of image. Performance analysis reveals that the proposed method significantly enhances the image contrast, reduces the color cast and meanwhile, keeps the computational consumption low.

Strathnet—a local area network

1981 ◽  
Vol 1 (1) ◽  
pp. 21 ◽  
Author(s):  
David Hutchison ◽  
Doug Shepherd
Keyword(s):  
Local Area Network ◽  
Local Area ◽  
Area Network

A Local Area Network for Medical Research; Planning, Realization and Experience

1991 ◽  
Vol 30 (01) ◽  
pp. 53-64 ◽  
Author(s):  
R. Schosser ◽  
C. Weiss ◽  
K. Messmer
Keyword(s):  
Medical Research ◽  
Word Processing ◽  
Local Area Network ◽  
Local Area ◽  
Area Network ◽  
Test Installation ◽  
Cost Performance ◽  
The Public ◽  
On Line ◽  
The University

This report focusses on the planning and realization of an interdisciplinary local area network (LAN) for medical research at the University of Heidelberg. After a detailed requirements analysis, several networks were evaluated by means of a test installation, and a cost-performance analysis was carried out. At present, the LAN connects 45 (IBM-compatible) PCs, several heterogeneous mainframes (IBM, DEC and Siemens) and provides access to the public X.25 network and to wide-area networks for research (EARN, BITNET). The network supports application software that is frequently needed in medical research (word processing, statistics, graphics, literature databases and services, etc.). Compliance with existing “official” (e.g., IEEE 802.3) and “de facto” standards (e.g., PostScript) was considered to be extremely important for the selection of both hardware and software. Customized programs were developed to improve access control, user interface and on-line help. Wide acceptance of the LAN was achieved through extensive education and maintenance facilities, e.g., teaching courses, customized manuals and a hotline service. Since requirements of clinical routine differ substantially from medical research needs, two separate networks (with a gateway in between) are proposed as a solution to optimally satisfy the users’ demands.

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