• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.741-744
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• 2008

In this paper, tone mapping method by local contrast and detail enhancement for High Dynamic Range (HDR) is proposed. By applying Piecewise Dynamic Range Histogram Adjustment (PDRHA) and Detail Enhancement Volume (DEV) with decomposed layers, tone mapping is performed effectively. The experimental results show that the proposed method preserves local contrast and overall impression with naturalness of original images.

• 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.

• Korean Journal of Digital Imaging in Medicine
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• v.15 no.1
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• pp.27-31
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• 2013

Perfusion MR imaging is how to use exogenous and endogenous contrast agent. Exogenous perfusion MRI methods which are dynamic susceptibility contrast using $T2^*$ effect and dynamic contrast-enhanced using T1 weighted image after injection contrast media. An endogenous perfusion MRI method which is arterial spin labeling using arterial blood flow in body. In order to exam perfusion MRI in human, technical access are very important according to disease conditions. For instance, dynamic susceptibility contrast is used in patients with acute stroke because of short exam time, while dynamic susceptibility contrast or dynamic contrast enhancement provides the various perfusion information for patients with tumor, vascular stenosis. Arterial spin labeling is useful for children, women who are expected to be pregnant. In this regard, perfusion MR imaging is required to understanding, and the author would like to share information with clinical users

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.1
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• pp.14-21
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• 2008

In this paper, we propose an adaptive contrast enhancement method using dynamic range segmentation. Histogram Equalization (HE) method is widely used for contrast enhancement. However, histogram equalization method is not suitable for commercial display because it may cause undesirable artifacts due to the significant change in brightness. The proposed algorithm segments the dynamic range of the histogram and redistributes the pixel intensities by the segment area ratio. The proposed method may cause over compressed effect when intensity distribution of an original image is concentrated in specific narrow region. In order to overcome this problem, we introduce an adaptive scale factor. The experimental results show that the proposed algorithm suppresses the significant change in brightness and provides wide histogram distribution compared with histogram equalization.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.913-914
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• 2008

This paper presents a method of adaptive image enhancement with dynamic range compression and contrast enhancement. The dynamic range compression is to adaptively enhance the dark area using illumination component of DCT compression block. The contrast enhancement is to modify the image contrast using retinex theory that uses the HVS properties. The block artifacts and other noises, caused by processing in the compression domain, were removed by after processing.

• Korean Journal of Radiology
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• v.1 no.4
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• pp.185-190
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• 2000

Objective: To document the imaging findings of hepatic cavernous hemangioma detected in cirrhotic liver. Materials and Methods: The imaging findings of 14 hepatic cavernous hemangiomas in ten patients with liver cirrhosis were retrospectively analyzed. A diagnosis of hepatic cavernous hemangioma was based on the findings of two or more of the following imaging studies: MR, including contrast-enhanced dynamic imaging (n = 10), dynamic CT (n = 4), hepatic arteriography (n = 9), and US (n = 10). Results: The mean size of the 14 hepatic hemangiomas was 0.9 (range, 0.5-1.5) cm in the longest dimension. In 11 of these (79%), contrast-enhanced dynamic CT and MR imaging showed rapid contrast enhancement of the entire lesion during the early phase, and hepatic arteriography revealed globular enhancement and rapid filling-in. On contrast-enhanced MR images, three lesions (21%) showed partial enhancement until the 5-min delayed phases. US indicated that while three slowly enhancing lesions were homogeneously hyperechoic, 9 (82%) of 11 showing rapid enhancement were not delineated. Conclusion: The majority of hepatic cavernous hemangiomas detected in cirrhotic liver are small in size, and in many, hepatic arteriography and/or contrast-enhanced dynamic CT and MR imaging demonstrates rapid enhancement. US, however, fails to distinguish a lesion of this kind from its cirrhotic background.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.917-918
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• 2008

Histogram Equalization (HE) method is widely used for contrast enhancement. However, HE often introduce washed out appearance or color distortion due to the over enhancement in contrast. In this paper, Dynamic Range Separate Histogram Equalization (DRSHE) is proposed for contrast enhancement. DRSHE reconfigures the dynamic range of histogram using probability distribution ratio. The experimental results show that DRSHE suppresses the washed out appearance or color distortion and preserves naturalness of the original image compared with conventional methods.

• 전자공학회논문지 IE
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• v.48 no.2
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• pp.32-39
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• 2011

The output image of the uncooled thermal infrared camera is difficult the identification of target because of the limited dynamic range and the various noises. Retinex algorithm based on the theory of the human visual perception is known to be effective contrast enhancement technique. However, the image quality is insufficient when it is adopted to the narrow dynamic range image as the infrared image. In this paper, we propose the revised retinex algorithm to enhance the contrast of the infrared image. To improve the contrast enhancement performance, we designed the new dynamic range compression function instead of log function. To reduce the noise and compensate the loss of edge, we added the contrast compensation procedure in the MSR image generation process. According to the output picture comparing and numerical analysis, the proposed algorithm shows the better contrast enhancement performance and the more suitable method for the infrared image enhancement.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.1
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• pp.35-44
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• 2015

The main purpose of image enhancement is to improve certain characteristics of an image to improve its visual quality. This paper proposes a method for image contrast enhancement that can be applied to both medical and natural images. The proposed algorithm is designed to achieve contrast enhancement while also preserving the local image details. To achieve this, the proposed method combines local image contrast preserving dynamic range compression and contrast limited adaptive histogram equalization (CLAHE). Global gain parameters for contrast enhancement are inadequate for preserving local image details. Therefore, in the proposed method, in order to preserve local image details, local contrast enhancement at any pixel position is performed based on the corresponding local gain parameter, which is calculated according to the current pixel neighborhood edge density. Different image quality measures are used for evaluating the performance of the proposed method. Experimental results show that the proposed method provides more information about the image details, which can help facilitate further image analysis.

• 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.