• Journal of Multimedia Information System
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• v.4 no.2
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• pp.65-73
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• 2017

This paper proposes a method to improve the image quality by designing Unsharp Mask Filter (UMF) based on Retinex theory which controls the frequency pass characteristics adaptively. Conventional unsharp masking technique uses blurring image to emphasize sharpness of image. Unsharp Masking(UM) adjusts the original image and sigma to obtain a high frequency component to be emphasized by the difference between the blurred image and the high frequency component to the original image, thereby improving the contrast ratio of the image. In this paper, we design a Unsharp Mask Filter(UMF) that can process the contrast ratio improvement method of Unsharp Masking(UM) technique with one filtering. We adaptively process the contrast ratio improvement using Unsharp Mask Filter(UMF). We propose a method based on Retinex theory for adaptive processing. For adaptive filtering, we control the weights of Unsharp Mask Filter(UMF) based on the human visual system and output more effective results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.10
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• pp.1934-1936
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• 2015

This paper proposes an optimal relay selection and adaptive throughput enhancement scheme utilizing superposition modulation in cooperative communication. The optimal relay is selected and the channel state is estimated by utilizing superposition modulation. The source determines the number of superimposed signal in accordance with the estated channel state. As a result, throughput is increased in accordance with the channel state.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.361-362
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• 2007

We propose a contrast-controlled feature detection approach for steel radiograph image. X-ray images are low contrast, dark and high noise image. So, It is not simple to detect defects directly in automated radiography inspection system. Contrast enhancement, histogram equalization and median filter are the most frequently used techniques to enhance the X-ray images. In this paper, the adaptive control method based on contrast limited histogram equalization is compared with several histogram techniques. Through comparative analysis, CLAHE(contrast controlled adaptive histogram equalization) can enhance detection of defects better.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.1
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• pp.51-57
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• 2005

In this paper, we propose an adaptive contrast control method for the flat real-time processing. The proposed method has employed probability density function(PDF) in order to control a sudden change in image-brightness. In addition, the proposed algerian obtains the maximum contrast without affecting the processed image. In order to reduce hardware complexity, we have utilized approximated CDF based on sampling values. Visual test and standard deviation of their histogram have been introduced to evaluate the resultant output images of at: proposed method and the original ones.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.2
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• pp.95-102
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• 2008

This paper proposes an adaptive speech enhancement system based on an auditory system to enhance speech that is degraded by various background noises. As such, the proposed system detects voiced and unvoiced sections, adaptively adjusts the coefficients for both the lateral inhibition and the amplitude component according to the detected sections for each input fame, then reduces the noise signal using a time-delay neural network. Based on measuring the signal-to-noise ratio, experiments confirm that the proposed system is effective for speech degraded by various noises.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.10
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• pp.77-83
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• 2016

This paper presents an adaptive retinex algorithm using skewness for contrast enhancement of color images. In order to estimate the degree of low contrast of an image, skewness of luminance of an observed image is used to define a parameter, and a non-linear function is proposed to compensate the reflectance using the parameter and estimated reflectance. In addition, determination of gain and offset of the non-linear function is addressed using statistics of the estimated reflectance. The relation between an observed luminance and the compensated luminance is used to compensate color components with the reduction of computational cost. The experimental results show that the proposed algorithm has the capability to effectively improve the contrast without color distortion.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.8
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• pp.160-171
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• 1994

The wide dynamic range and severely attenuated contrast in mediastinal area appearing in typical chest radiographs have often caused difficulties in effective visualization and diagnosis of lung diseases. This paper proposes a new adaptive image enhancement technique which potentially solves this problem and there by improves observer performance through image processing. In the proposed method image processing is applied to the chest radiograph with different processing parameters for the lung field and mediastinum adaptively since there are much differences in anatomical and imaging properties between these two regions. To achieve this the chest radiograph is divided into the lung and mediastinum by gray level thresholding using the cumulative histogram and the dynamic range compression and local contrast enhancement are carried out selectively in the mediastinal region. Thereafter a gray scale transformation is performed considering the JND(just noticeable difference) characteristic for effective image displa. The processed images showed apparenty improved contrast in mediastinum and maintained moderate brightness in the lung field. No artifact could be observed. In the visibility evaluation experiment with 5 radiologists the processed images with better visibility was observed for the 5 important anatomical structures in the thorax.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.11 no.2
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• pp.33-42
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• 2003

In this paper, we propose an enhancement of the ultrasonic image for non-destructive inspection of aircraft composite materials. The ultrasonic images are corrupted by a speckle noise which has the characteristic of granular pattern noise and is in all types of coherent imaging systems, the signal independent and multiplicative noise. In this paper, we derive a filter, called the AWLF(Adaptive Window Log Filter), from the nature of the speckle. The filter is made of the MEAN Filter in the edge region and Log Filter in the flat or noise region. To make a distinction between edge and flat region, we calculate the inclination around the local window instead of computing the local statistics of pixels such as local mean ${\bar{M}}$ and standard deviation ${\sigma}_s$. According to the obtained region, edge region is performed by the mean filter and flat region by the Log filter. Performance of the proposed filter is evaluated by the Enhanced Factor$(F_e)$ and the Speckle Index(SI).

• The KIPS Transactions:PartB
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• v.16B no.4
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• pp.263-270
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• 2009

Histogram Equalization (HE) is a very popular technique for enhancing the contrast of an image. HE stretches the dynamic range of an image using the cumulative distribution function of a given input image, therefore improving its contrast. However, HE has a well-known problem : when HE is applied for the contrast enhancement, there is a significant change in brightness. To resolve this problem, we propose An Adaptive Contrast Enhancement Algorithm using Subhistogram Area-Ratioed Histogram Redistribution, a new method that helps reduce excessive contrast enhancement. This proposed algorithm redistributes the dynamic range of an input image using its mean luminance value and the ratio of sub-histogram area. Experimental results show that by this redistribution, the significant change in brightness is reduced effectively and the output image is able to preserve the naturalness of an original image even if it has a poor histogram distribution.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.958-964
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• 2010

Histogram Equalization(HE) is one of the well known methods for contrast enhancement. but, it did not applied directly due to side effects such as significant change in brightness or washed out appearance. Many conventional method try to overcome this problem but they did not guarantee various image or depend on user define parameter. In this paper, an Adaptive histogram Compensated Histogram Equalization(ACHE) is proposed for contrast enhancement. ACHE has a parameter that based on median of input image. Histogram of input image is compensated according to parameter. And then finally compensated histogram is equalized. Experimental results show that proposed method suppresses side effects such as detail loss or washed out appearance. Moreover, parameter calculated automatically with low computation complexity. As a result, it could applies FPD directly.