• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.5127-5133
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• 2010

In this paper, an efficient contrast enhancement algorithm using histogram specification is proposed. Histogram equalization and its modified methods have been effective techniques for contrast enhancement. However, they often result in excessive contrast enhancement. Besides conventional histogram specification also has a problem to get the desired histogram. We propose a method that utilizes a simple high frequency filter to get the desired histogram. The proposed technique not only produces better visual results than conventional contrast enhancement techniques, but is also adaptively adjusted to the statistical characteristics of the image.

• 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.

• Journal of Veterinary Clinics
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• v.38 no.3
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• pp.135-142
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• 2021

The aim of this study was to evaluate the contrast effect if a saline flush following low-volume contrast medium bolus improves vascular and parenchymal enhancement using a saphenous vein in abdominal CT for small animals. Six clinically healthy beagle dogs underwent abdominal contrast-enhanced CT. They were divided into nine groups (each group, n = 6), according to the volume of contrast medium 1, 2, and 3 mL/kg, and volume of the saline solution 0, 5, and 10 mL. Dynamic CT scanning was performed at the hepatic hilum level. The maximum contrast enhancement, time to maximum enhancement, and time to equilibrium phase were calculated from the time attenuation curves. Mean attenuation values for all groups were measured in the aorta, portal vein, and liver. After contrast enhancement, grading of image quality regarding surrounding artifacts and evaluation of the hepatic hilum structures was performed. For comparison of the effect of the contrast material and saline solution doses, differences in mean attenuation values between the contrast medium 2 mL/kg without saline flush group and the remaining groups, and between contrast medium 3 mL/kg without saline flush group and the remaining groups, were analyzed for statistical significance. There were no significant differences between with and without saline flushing at the same contrast medium dose groups. There were no significant differences in peak values between the 3 mL/kg dose of contrast medium alone and the 2 mL/kg dose of contrast medium with saline solution flush. However, there was a significant difference in peak values between the 3 mL/kg dose of the contrast medium without the saline flush group and the 2 mL/kg dose of the contrast medium alone group. Grades of the artifacts were not significantly different in the saline flush regardless of the dose of the contrast medium. Using 2 mL/kg of contrast medium with saline solution flush resulted in similar liver parenchyma attenuation, compared with using 3 mL/kg of contrast medium without saline solution flush. In CT evaluation of hepatic parenchymal diseases, using 2 mL/kg of contrast medium with saline solution flush may yield decreased risk of contrast nephropathy and cost-saving.

• 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.

• Journal of IKEEE
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• v.11 no.4
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• pp.307-314
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• 2007

In this paper, we propose an image contrast enhancement algorithm for an LCD TV. The proposed algorithm consists of two processes: the image segmentation process and the tone curve control process. The first process uses an automatic threshold technique to decompose an input image into two regions and then utilizes a hierarchical structure for real-time processing. The second process generates a gray level tone curve for contrast enhancement using a weighted sum of average tone curves for two segmented regions. Experimental result shows that the proposed algorithm outperforms the conventional contrast enhancement methods for an LCD TV.

• Journal of Korea Multimedia Society
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• v.8 no.9
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• pp.1187-1194
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• 2005

In this paper, new contrast enhancement algorithms that use temporal decimation method and approximated CDF(Cumulative Distribution Function) are proposed. They reduce the amount of computation which is required for image contrast enhancement. Simulation results show that the algorithms can achieve significant reduction in the computational cost and the hardware complexity. Visual test and standard deviation of their histogram have been introduced to evaluate the resultant output images of the proposed method and the original ones.

• 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.

• Journal of Korea Multimedia Society
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• v.11 no.6
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• pp.737-745
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• 2008

In this paper, a novel neighborhood metric of histogram equalization (HE) algorithm for contrast enhancement is presented. We present a refinement of HE using neighborhood metrics with a general framework which orders pixels based on a sequence of sorting functions which uses both global and local information to remap the image greylevels. We tested a novel sorting key with the suggestion of using the original image greylevel as the primary key and a novel neighborhood distinction metric as the secondary key, and compared HE using proposed distinction metric and other HE methods such as global histogram equalization (GHE), HE using voting metric and HE using contrast difference metric. We found that our method can preserve advantages of other metrics, while reducing drawbacks of them and avoiding undesirable over-enhancement that can occur with local histogram equalization (LHE) and other methods.

• Journal of Korea Multimedia Society
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• v.14 no.11
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• pp.1365-1372
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• 2011

This paper proposes a cognitive contrast enhancement algorithm based on the non-linear masking to advance low cognitive contrast in dark regions of images. In order to improve brightness in dark regions of an image, we propose a new contrast enhancement algorithm based on the non-linear masking using regional adaptive parameters of an image. For performance evaluation of the proposed method, chromaticity and saturation comparison as a quantitative assessment and z-score comparison as a qualitative assessment were executed between test images and their simulated images by SSR, MSR, a conventional non-linear masking and the proposed method, respectively. As a result, the proposed method showed low chromaticity and saturation difference and improved cognitive contrast for the three methods.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1236-1247
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• 2016

Recently, the level set has become a popular method in many research fields. The main reason is that it can be modified into many variants. One such case is our proposed method. We describe a contrast-enhancement method to segment the hippocampal region from the background. However, the hippocampus region has quite similar intensities to the neighboring pixel intensities. In addition, to handle the inhomogeneous intensities of the hippocampus, we used a bias correction before hippocampal segmentation. Thus, we developed a contrast-enhanced bias-corrected distance-regularized level set (CBDLS) to segment the hippocampus in magnetic resonance imaging (MRI). It shows better performance than the distance-regularized level set evolution (DLS) and bias-corrected distance-regularized level set (BDLS) methods in 33 MRI images of one normal patient. Segmentation after contrast enhancement and bias correction can be done more accurately than segmentation while not using a bias-correction method and without contrast enhancement.