• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.1
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• pp.99-107
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• 2019

Retinex-based image enhancement is a technique that utilizes the property that the human visual characteristics are sensitive to the difference from the surrounding pixel value rather than the pixel value itself. These Retinex-based algorithms show different characteristics of the improved image depending on the applied color space or gamma correction. In this paper, we set eight different experimental conditions according to the application of color space and gamma correction, and analyze the objective and subjective performance of each Retinex based image enhancement algorithm and apply it to the implementation of Retinex based algorithm. In the case of gamma correction, quantitative low entropy images and low contrast images are obtained. The application of Retinex technique in HSI color space rather than RGB color space is found to be high in overall subjective image quality as well as maintaining color.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.9-16
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• 2018

Images with lower illumination from the light source or with dark regions due to shadows, etc., can improve subjective image quality by using retinex-based image enhancement schemes. The retinex theory is a method that recognizes the relative lightness of a scene, rather than recognizing the brightness of the scene. The way the human visual system recognizes a scene in a specific position can be in one of several methods: single-scale retinex, multi-scale retinex, and multi-scale retinex with color restoration (MSRCR). The proposed method is based on the MSRCR method, which includes a color restoration step, which consists of three phases. In the first phase, the existing MSRCR method is applied. In the second phase, the dynamic range of the MSRCR output is adjusted according to its histogram. In the last phase, the proposed method transforms the retinex output value into the display dynamic range using a logarithm transformation function considering human visual system characteristics. Experimental results show that the proposed algorithm effectively increases the subjective image quality, not only in dark images but also in images including both bright and dark areas. Especially in a low lightness image, the proposed algorithm showed higher performance improvement than the conventional approaches.

• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.61-69
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• 2011

This paper proposes a new algorithm that improve color component of compensated image using Retinex method for back-light image. A back-light image has two regions, one of the region is too bright and the other one is too dark. If an back-light image is improved contrast using Retinex method, it loses color information in the part of brightness of the image. In order to make up loss information, proposed algorithm adds color components from original image. The histogram can be divided three parts that brightness, darkness, midway using K-mean (k=3) algorithm. For the brightness, it is used color information of the original image. For the darkness, it is converted using by Retinex method. The midway region is mixed between original image and Retinex result image in the ratio of histogram. The ratio is determined by distance from dark area. The proposed algorithm was tested on nature back-light images to evaluate performance, and the experimental result shows that proposed algorithm is more robust than original Retinex algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8C
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• pp.497-504
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• 2011

This paper presents an adaptive retinex algorithm, In order to solve typical problems of retinex algorithm such as expensive computational cost, halo artifact, and color distortion, a function of skewness that represents a statistical distribution of pixels is defined to compensate contrast and color distortion. The experimental results show that the proposed algorithm leads to subjectively better performance than typical retinex algorithm, and that the proposed algorithm has the capability to reduce approximately 40% computational cost than typical retinex algorithm.

• Journal of IKEEE
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• v.17 no.4
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• pp.478-483
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• 2013

This paper presents an adaptive Retinex algorithm for improving dynamic range of image representation. The proposed Retinex algorithm detects degraded brightness by using skewness and the degraded components are compensated with local statistics. In particular, we propose a new compensation function for dynamic range so that effectinve image representation can be achieved. Experimental results show that the proposed algorithm has the capability to improve the dynamic range with reduction of color degradation.

• Journal of Korea Multimedia Society
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• v.16 no.1
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• pp.29-41
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• 2013

The digital camera is impossible to preserve the appearance of a scene containing high dynamic range due to a limitations of the sensing hardware. The Retinex was proposed on the purpose to solve these problems. While the Retinex enhances visibility and color constancy, it sometimes suffers from color distortion, halo effect and reduced global contrast. This paper presents an advanced Retinex algorithm working on the YCbCr color coordinate to reduce the processing time and to improve the global contrast and color. Simulation results show that our algorithm significantly reduces the total processing time, and provide the superior result image by improving the global contrast and color consistency as well as by reducing the halo effect around the boundaries.

• Journal of Broadcast Engineering
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• v.17 no.5
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• pp.851-863
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• 2012

Retinex algorithm enhances the contrast of image through visibility improvement. However, the conventional Retinex methods may produces color distortions due to error of hue representation and over-saturation since the methods work in RGB color space. In this paper, we propose a new Retinex algorithm with color correction, which improves contrast by using MSR(Multi-Scale Retinex) working in YCbCr color space and adaptively compensates the color saturation based on the maximum color difference table. Our algorithm maps the color difference signals to the correct gamut to prevent over-saturation phenomenon by considering the correlation between luminance and hue dependent saturation. Simulations results show that the proposed method gives better color improvement compared to the conventional methods.

• 전자공학회논문지 IE
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• v.46 no.4
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• pp.31-41
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• 2009

The Image sensor of digital still camera has a limited dynamic range. In high dynamic range scenes, a picture often turns out to be underexposed or overexposed. Retinex algorithm based on the theory of the human visual perception is known to be effective contrast enhancement technique. However, it happens the unbalanced contrast enhancement which is the global contrast increased, and the local contrast decreased in the high dynamic range scenes. In this paper, to enhance the both global and local contrast, we propose the weight mapping retinex algorithm. Weight map is composed of the edge and exposure data which are extracted in the each retinex image, and merged with the retinex images in the fusion processing. According to the output picture comparing and numerical analysis, the proposed algorithm gives the better output image with the increased global and local contrast.

• Journal of Korea Multimedia Society
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• v.20 no.9
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• pp.1481-1490
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• 2017

This paper presents an image quality enhancement algorithm for dark image acquired under poor lighting condition. Various retinex algorithms which are human perception-based image processing methods were proposed to solve this problem. Although MSR(Multi-Scale Retinex) among these algorithm works well under most lighting condition, it shows color degradation because their separate nonlinear processing of RGB color channels. To compensate for the loss of the color, MSRCR(Multi-Scale Retinex with Color Restoration) was proposed. However, it requires high computational load and has additional parameters that need to be adjusted according to input image. In order to overcome this problem, a new retinex algorithm based on MSR is proposed in this paper. The proposed method consists of V channel MSR, saturation correction, and separate contrast enhancement process. Experimental results show that the subjective and objective image quality of the proposed method better than those of the conventional methods.

• Journal of the Korea Society of Computer and Information
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• v.15 no.8
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• pp.31-39
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• 2010

The paper proposes the median filter based Retinex algorithm to detect the lanes in a foggy image. Whether an input image is foggy or not is determined by analyzing the histogram in the pre-defined ROI(Region of Interest). If the image is determined as a foggy one, then it is improved by the median filter based Retinex algorithm. By replacing the Gaussian filter by the median filter in the Retinex algorithm, the processing time can be reduced and the lane features can be detected more robustly. Once the enhanced image is acquired, the binarization based on multi-threshold and the labeling operations are applied. Finally, it detects the lane information using the size and direction parameters of the detected lane features. The proposed algorithm has been evaluated by using various foggy images collected on different road conditions to prove that it detects lanes more robustly in most cases than the conventional methods.