• Journal of Korea Multimedia Society
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• v.11 no.4
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• pp.462-470
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• 2008

This study applies fuzzy functions to improve image quality under the assumption that uncertainty of image information due to low contrast is based on vagueness and ambiguity of the brightness pixel values. To solve the problem of low contrast images whose brightness distribution is inclined, we use the k-means algorithm as a parameter of the fuzzy function, through which automatic critical points can be found to differentiate objects from background and contrast between bright and dark points can be improved. The fuzzy function is presented at the three main stages presented to improve image quality: fuzzification, contrast enhancement and defuzzification. To measure improved image quality, we present the fuzzy index and entropy index and in comparison with those of histogram equalization technique, it shows outstanding performance.

• Journal of Korea Multimedia Society
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• v.21 no.9
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• pp.1044-1051
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• 2018

In this paper, we propose a new method to improve low light image. In order to improve the image quality of a night image with a moving object as much as the quality of a daytime image, the following tasks were performed. Firstly, we reduce the noisy of the input night image and improve the night image by the tone mapping method. Secondly, we segment the input night image into a foreground with motion and a background without motion. The motion is detected using both the difference between the current frame and the previous frame and the difference between the current frame and the night background image. The background region of the night image takes pixels from corresponding positions in the daytime image. The foreground regions of the night image take the pixels from the corresponding positions of the image which is improved by the tone mapping method. Experimental results show that the proposed method can improve the visual quality more clearly than the existing methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3245-3271
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• 2016

To obtain well-dehazed images at the receiver while sustaining low bit rates in the transmission pipeline, this paper investigates the effects of image dehazing methods using dehazing contrast-enhancement filters on image compression for surveillance systems. At first, this paper proposes a novel image dehazing method by using a new method of calculating the transmission function—namely, the direct denoising method. Next, we deduce the dehazing effects of the direct denoising method and image dehazing method based on dark channel prior (DCP) on image compression in terms of ringing artifacts and blocking artifacts. It can be concluded that the direct denoising method performs better than the DCP method for decompressed (reconstructed) images. We also improve the direct denoising method to obtain more desirable dehazed images with higher contrast, using the saliency map as the guidance image to modify the transmission function. Finally, we adjust the parameters of dehazing contrast-enhancement filters to obtain a corresponding composite peak signal-to-noise ratio (CPSNR) and blind image quality assessment (BIQA) of the decompressed images. Experimental results show that different filters have different effects on image compression. Moreover, our proposed dehazing method can strike a balance between image dehazing and image compression.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.20 no.1
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• pp.37-44
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• 2016

Ultrasonic imaging is the most widely modality among modern imaging device for medical diagnosis. Nevertheless, medical ultrasound images suffer from speckle noise and low contrast. In this paper, we propose probabilistic edge map for ultrasound image edge enhancement using automatic alien algorithm. The proposed method used applied speckle reduced ultrasound imaging for edge improvement using sequentially acquired ultrasound imaging. To evaluate the performance of method, the similarity between the reference and edge enhanced image was measured by quantity analysis. The experimental results show that the proposed method considerably improves the image quality with region edge enhancement.

• Korean Journal of Cognitive Science
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• v.25 no.1
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• pp.51-71
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• 2014

This paper presents an image enhancement method in real road traffic scenes. The images captured by the camera on the car cannot keep the color constancy as illumination or weather changes. In the real environment, these problems are more worse at back light conditions and at night that make more difficult to the applications of the vision-based intelligent vehicles. Using the existing image enhancement methods without considering the position and intensity of the light source and their geometric relations the image quality can even be deteriorated. Thus, this paper presents a fast and effective method for image enhancement resembling human cognitive system which consists of 1) image preprocessing, 2) color-contrast evaluation, 3) alpha blending of over/under estimated image and preprocessed image. An input image is first preprocessed by gamma correction, and then enhanced by an Automatic Color Enhancement(ACE) method. Finally, the preprocessed image and the ACE image are blended to improve image visibility. The proposed method shows drastically enhanced results visually, and improves the performance in traffic sign detection of the vision based intelligent vehicle applications.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.30-35
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• 2010

This paper presents a quality enhancement of images by using a histogram equalization based on the symmetric logistic function. The histogram equalization is a simple and effective spatial processing method that it enhances the quality by adjusting the brightness of image. The logistic function that is a sigmoidal nonlinear transformation function, is applied to non-linearly enhance the brightness of the image according to its intensity level frequency. We propose a flexible and symmetrical logistic function by only using the intensity with maximum frequency in an histogram and the total number of pixels. The proposed function decreases the computation load of an exponential function in the traditional logistic function. The proposed method has been applied for equalizing 5 images with a different resolution and histogram distribution. The experimental results show that the proposed method has the superior enhancement performances compared with the source images and the traditional global histogram equalization, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3188-3207
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• 2017

In this paper, we propose an image enhancement algorithm to improve license plate extraction rate in various environments (Day Street, Night Street, Underground parking lot, etc.). The proposed algorithm is composed of image enhancement algorithm and license plate extraction algorithm. The image enhancement method can improve an image quality of the degraded image, which utilizes a histogram information and overall gray level distribution of an image. The proposed algorithm employs an interpolated probability distribution value (PDV) in order to control a sudden change in image brightness. Probability distribution value can be calculated using cumulative distribution function (CDF) and probability density function (PDF) of the captured image, whose values are achieved by brightness distribution of the captured image. Also, by adjusting the image enhancement factor of each part region based on image pixel information, it provides a function that can adjust the gradation of the image in more details. This processed gray image is converted into a binary image, which fuses narrow breaks and long thin gulfs, eliminates small holes, and fills gaps in the contour by using morphology operations. Then license plate region is detected based on aspect ratio and license plate size of the bound box drawn on connected license plate areas. The images have been captured by using a video camera or a personal image recorder installed in front of the cars. The captured images have included several license plates on multilane roads. Simulation has been executed using OpenCV and MATLAB. The results show that the extraction success rate is more improved than the conventional algorithms.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.18-26
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• 2009

Image resolution enhancement algorithm is a basic technique for image enlargement and restoration. The main problem is the image quality degradation such as blurring or blocking effects. In this paper, we propose loss information estimation and image resolution enhancement method using low level interpolation method. In the proposed method, loss information is computed by downsampling -interpolation process of obtained low resolution image. We estimate loss information of high resolution image using interpolation of the computed loss information. Lastly, we add up interpolated high resolution image and the estimated loss information which is applied a weight factor. Our experiments obtained the average PSNR 1.4dB which is improved results better than conventional algorithm. Also subjective image quality is more clearness and distinctness. The proposed method may be helpful for various video applications which required improvement of image.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.140-143
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• 2004

The mage enhancement of dental On image using wavelet coefficients is presented. The processing is that make gray image from On image by preprocessing, extract high frequency from detail coefficient after acquisition detail coefficient by wavelet transform and emphasize edge appling input image. Experimental results show that enhanced contrast of dental On image, improved mage quality.

• Journal of the Korean Society of Industry Convergence
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• v.13 no.1
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• pp.23-30
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• 2010

This paper presents a histogram equalization based on the nonlinear transformation function for enhancing the quality of medical images. The nonlinear transformation function is applied to adaptively equalize the brightness of the image according to its intensity level frequency. The logistic function is used as a nonlinear transformation function, which is calculated by only using the intensity level with maximum frequency and the maximum intensity level in an histogram, and the total number of pixels. The proposed method has been applied for equalizing 8 medical images with a different resolution and histogram distribution. The experimental results show that the proposed method has the superior enhancement performances compared with the conventional histogram equalization. And the proposed histogram equalization can be used in various multimedia systems in real-time.