• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.12
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• pp.1054-1064
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• 2012

HDR (high dynamic range) tone mapping algorithms are used in image processing that reduces the dynamic range of an image to be displayed on LDR (low dynamic range) devices properly. The retinex is one of the tone mapping algorithms to provide dynamic range compression, color constancy, and color rendition. It has been developed through multi-scale methods and luminance-based methods. Retinex algorithms still have drawbacks such as the emphasized noise and desaturation. In this paper, we propose a multi scale tone mapping algorithm for enhancement of contrast, saturation, and noise of HDR rendered images based on visual brightness functions. In the proposed algorithm, HSV color space has been used for preserving the hue and saturation of images. And the algorithm includes the estimation of minimum and maximum luminance level and a visual gamma function for the variation of viewing conditions. And subjective and objective evaluations show that proposed algorithm is better than existing algorithms. The proposed algorithm is expected to image quality enhancement in some fields that require a improvement of the dynamic range due to the changes in the viewing condition.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.829-830
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• 2008

In modern days, many of the images are captured by using various devices, such as PDA, digital camera, or cell phone camera. Because all these devise have a limited dynamic range, images captured in real world scenes with high dynamic ranges usually exhibit poor visibility and low contrast, which may make important image features lost or hard to tell by human viewers. In this paper, the efficient color image enhancement method is presented. Experimental result show that the proposed method yields better performance of color enhancement over the previous work for test color images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.270-275
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• 2018

Method for improving the image quality are divided into a tone mapping method and a retinex theory based method. Typical example of the image quality enhancement method using tone mapping method is one using image characteristics like histogram. In this paper, we propose a hardware design of real-time wide dynamic range algorithm based on tone mapping method for image quality enhancement. The proposed method divides the image into the luminance and chroma components and then improves the chroma region based on the variation of the luminance component. Adding to that, it is designed to be compatible with the existing 8-bit signal, using high quality image with 12-bit extended signal according to the desired flow. As a result of simulation, it is confirmed that the image quality is improved, and the hardware design is confirmed that the real-time operations is possible at the maximum frequency at 138.26MHz.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.1-7
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• 2011

In this paper, we propose the digital image enhancement method including local tone reproduction and preservation of the hue. In recent studies, an integrated multi-scale retinex (IMSR) has produced great naturalness in the resulting images through enhancement of visibility in dark area in input images. However, most methods, including IMSR, work in RGB color spaces. As such, this produces hue distortion from the perspective of the human visual system, that is, hue distortion in CIELAB color space. Accordingly, this paper proposes an tone reproduction and enhancement of saturation method in a device-independent color space, CIELAB, to preserve the hue and obtain a high contrast and naturalness. First, to achieve the desired objectives, the IMSR is then applied to only the $L^*$ values in CIELAB color space, normalization, and simple mapping function, thereby preserving the balance of the color components and enhancement of visibility. Then, saturation adjustment is performed by applying the ratio of the chroma variation at the sRGB gamut boundary according to the corrected luminance. In experiments, the proposed method is shown to improve the visibility in dark shadows and bright regions in the resulting images and reduce any color distortion then preference test are performed.

• Journal of IKEEE
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• v.25 no.1
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• pp.139-147
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• 2021

This paper introduces an image decomposition-based deep learning method and loss function to improve low-light images. In order to remove color distortion and halo artifact, illuminance channel of an input image is decomposed into reflectance and luminance channels, and a decomposition-based multiple structural deep learning process is applied to each channel. In addition, a mixed norm-based loss function is described to increase the stability and remove blurring in reconstructed image. Experimental results show that the proposed method effectively improve various low-light images.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.5095-5111
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• 2019

A multi-rotor Unmanned Aerial Vehicle (UAV) system is developed to solve the manhole cover detection problem for the infrastructure maintenance in the suburbs of big city. The visible light sensor is employed to collect the ground image data and a series of image processing and machine learning methods are used to detect the manhole cover. First, the image enhancement technique is employed to improve the imaging effect of visible light camera. An imaging environment perception method is used to increase the computation robustness: the blind Image Quality Evaluation Metrics (IQEMs) are used to percept the imaging environment and select the images which have a high imaging definition for the following computation. Because of its excellent processing effect the adaptive Multiple Scale Retinex (MSR) is used to enhance the imaging quality. Second, the Single Shot multi-box Detector (SSD) method is utilized to identify the manhole cover for its stable processing effect. Third, the spatial coordinate of manhole cover is also estimated from the ground image. The practical applications have verified the outdoor environment adaptability of proposed algorithm and the target detection correctness of proposed system. The detection accuracy can reach 99% and the positioning accuracy is about 0.7 meters.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.5
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• pp.741-749
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• 2022

Major space agencies are planning for the rover-based lunar exploration since water-ice was detected in permanently shadowed regions (PSR). Although sunlight does not directly reach the PSRs, it is expected that reflected sunlight sustains a certain level of low-light environment. In this research, the indoor testbed was made to simulate the PSR's lighting and topological conditions, to which low light enhancement methods (CLAHE, Dehaze, RetinexNet, GLADNet) were applied to restore image brightness and color as well as to investigate their influences on the performance of feature extraction and matching methods (SIFT, SURF, ORB, AKAZE). The experiment results show that GLADNet and Dehaze images in order significantly improve image brightness and color. However, the performance of the feature extraction and matching methods were improved by Dehaze and GLADNet images in order, especially for ORB and AKAZE. Thus, in the lunar exploration, Dehaze is appropriate for building 3D topographic map whereas GLADNet is adequate for geological investigation.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.6
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• pp.101-109
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• 2016

The images captured by digital still cameras or mobile phones are not always satisfactory because the devices have limited dynamic ranges compared with that of the real world. To cope with the problems, tone mapping function based methods and retinex theory based methods are studied. However, these methods generate a halo artifact or limited enhancement of global and local contrasts. The proposed method estimates illumination information used for image enhancement by optimizing a dynamic range of input image. The estimated illumination information has smoothness characteristic where the luminance is flat and does not have where the luminance changes to prevent the halo artifact. Additionally, the estimated illumination information and surrounding pixel values are considered when the tone mapping function is applied to overcome the limitations of the conventional tone mapping function approach. Experimental results show that the proposed algorithm outperforms the conventional methods on objective and subjective criteria.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.4
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• pp.948-953
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• 2015

Recently, the finger vein recognition based on NIR and CCD sensor camera is investigating the technology to identify a personal using by biometrics. The performance difference of finger vein recognition is generated according to methods that are to separate the vein and background from noises such as finger thickness, ambient light, skin temperature, etc. To improve these problems, in this study, we are proposing the methods for rotation, ROI extraction, and enhancement of vein image captured by NIR LED and CCD camera, and were evaluated performances of these methods. In results of the experiment, the accuracy of the proposed method for image rotation and ROI extraction was 99.8%. And the proposed filter bank method in vein enhancement has shown better performance than retinex algorithm. The proposed method for results of these experimentations will provide better recognition rate when applied to the preprocessing of finger vein recognition.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.83-90
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• 2023

Blurred image is an important factor in lowering image recognition rates in Computer vision. This mainly occurs when the camera is unstablely out of focus or the object in the scene moves quickly during the exposure time. Blurred images greatly degrade visual quality, weakening visibility, and this phenomenon occurs frequently despite the continuous development digital camera technology. In this paper, it replace the modified building module based on the Deep multi-patch neural network designed with convolution neural networks to capture details of input images and Attention techniques to focus on objects in blurred images in many ways and strengthen the image. It measures and assigns each weight at different scales to differentiate the blurring of change and restores from rough to fine levels of the image to adjust both global and local region sequentially. Through this method, it show excellent results that recover degraded image quality, extract efficient object detection and features, and complement color constancy.