• Korean Journal of Radiology
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• v.22 no.8
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• pp.1352-1368
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• 2021

Objective: For an accurate dynamic contrast-enhanced (DCE) MRI analysis, exact baseline T1 mapping is critical. The purpose of this study was to compare the pharmacokinetic parameters of DCE MRI using synthetic MRI with those using fixed baseline T1 values. Materials and Methods: This retrospective study included 102 patients who underwent both DCE and synthetic brain MRI. Two methods were set for the baseline T1: one using the fixed value and the other using the T1 map from synthetic MRI. The volume transfer constant (K^trans), volume of the vascular plasma space (v_p), and the volume of the extravascular extracellular space (v_e) were compared between the two methods. The interclass correlation coefficients and the Bland-Altman method were used to assess the reliability. Results: In normal-appearing frontal white matter (WM), the mean values of K^trans, v_e, and v_p were significantly higher in the fixed value method than in the T1 map method. In the normal-appearing occipital WM, the mean values of v_e and v_p were significantly higher in the fixed value method. In the putamen and head of the caudate nucleus, the mean values of K^trans, v_e, and v_p were significantly lower in the fixed value method. In addition, the T1 map method showed comparable interobserver agreements with the fixed baseline T1 value method. Conclusion: The T1 map method using synthetic MRI may be useful for reflecting individual differences and reliable measurements in clinical applications of DCE MRI.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1281-1287
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• 2016

This paper presents a method of single image dehazing and feature matching for aerial remote sensing images. In the case of a aerial image, transferring the information of the original image is difficult as the contrast leans by the haze. This also causes that the image contrast decreases. Therefore, a refined transmission map based on a hidden Markov random field. Moreover, the proposed algorithm enhances the accuracy of image matching surface-based features in an aerial remote sensing image. The performance of the proposed algorithm is confirmed using a variety of aerial images captured by a Worldview-2 satellite.

• Journal of Broadcast Engineering
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• v.22 no.5
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• pp.608-617
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• 2017

Methods of contrast enhancement have problem such as side effect of over-enhancement with non-gaussian histogram distribution, tradeoff enhancement efficiency against brightness preserving. In order to enhance contrast at various histogram distribution, segmentation to region with gaussian distribution and then enhance contrast each region. First, we segment an image into several regions using GMM(Gaussian Mixture Model)fitting by that k-mean clustering and EM(Expectation-Maximization) in $L^*a^*b^*$ color space. As a result region segmentation, we get the region map and probability map. Then we apply local contrast enhancement algorithm that mean shift to minimum overlapping of each region and preserve brightness histogram equalization. Experiment result show that proposed region based contrast enhancement method compare to the conventional method as AMBE(AbsoluteMean Brightness Error) and AE(Average Entropy), brightness is maintained and represented detail information.

• Korean Journal of Child Studies
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• v.14 no.2
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• pp.79-94
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• 1993

The purpose of this study was (1) to investigate whether linguistic contrast helps children map a new word into a specific semantic domain when a new word is introduced, (2) to examine the existence of a hierarchy of domains into which children will place a new word, (3) to examine whether children's existing lexicons affect how children map a new word. A total of 320 children from 3 to 6 years of age were drawn from Pusan, Korea. The children were divided into one of four age groups. There were 80 children in each age group. In each group, children were randomly assigned to one of four groups; the linguistic contrast group exposed to color, the linguistic contrast group exposed to shape, a label group and control group. All of the children were tested for production and comprehension of the new word. The results of this study were as follows; (1) The linguistic contrast helped children learn the meanings of a new word. Especially, children age 4 or more showed a significant effect for linguistic contrast; however, it was not sufficient to teach 3-year-old the correct, referent of a term. (2) There was a hierarchy of domains into which children mapped a new word. There was no significant effect for domains into which 3-year-old children mapped the new word, but from 4 years of age children showed a preference for assuming a new word refered to an object's shape rather than its color. (3) Children's existing lexicon had no effect, on how children comprehend a new word.

• Journal of Broadcast Engineering
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• v.18 no.5
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• pp.722-729
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• 2013

For low contrast images, a histogram equalization is possible to easily identify information when the intensity is concentrated in an image. Over contrast enhancement is the problem of generating an unnatural image cognitively because the focus of existing techniques was the contrast enhancement. In order to solve this problem, CLAHE method solves unnatural problems by limiting contrast using a maximum threshold. However, this method has an extra problem that concealed detail information in an image. This paper proposes a detail-map based on the multiple layers block overlapped histogram equalization in order to avoid loss of detail information. Loss of detail information has been made to minimize as combining images with limited contrast enhancement using a detail-map in each layers.

• Proceedings of the KSRS Conference
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• v.1
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• pp.368-371
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• 2006

A coastline is the boundary between land and ocean masses. Knowledge of coastline is essential for autonomous navigation, geographical exploration, coastal erosion monitoring and modelling, water line change, etc. Many methods have been researched to extract coastlines from the synthetic aperture radar (SAR) and optic images. Most methods were based on the intensity contrast between land and sea regions. However, in these methods, a coastline detection task was very difficult because of insufficient intensity contrast and the ambiguity in distinguishing coastline from other object line. In this paper, we propose an efficient method for the delineation of coastline using interferometric coherence values estimated from ERS tandem pair. The proposed method uses the facts that a tandem pair of ERS is acquired from a time interval of an accurate day and that the coherent and incoherent values in coherence map are land and water, respectively. The coherence map was generated from ERS tandem pair, filtered by MAP filter, and divided into land and water by the determination of threshold value that is based on the bimodality of the histogram. Finally, a coastline was detected by delineating the boundary pixels. There was a good visual match between the detected coastline and the manually contoured line. The interferometric coherence map will be helpful to identify land and water regions easily, and can be used to many applications that are related with a coastline.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2287-2312
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• 2018

Extracting key visual information from images containing natural scene is a challenging task and an important step for the visually impaired to recognize information based on tactile graphics. In this study, a novel method is proposed for extracting salient regions based on global contrast enhancement and saliency cuts in order to improve the process of recognizing images for the visually impaired. To accomplish this, an image enhancement technique is applied to natural scene images, and a saliency map is acquired to measure the color contrast of homogeneous regions against other areas of the image. The saliency maps also help automatic salient region extraction, referred to as saliency cuts, and assist in obtaining a binary mask of high quality. Finally, outer boundaries and inner edges are detected in images with natural scene to identify edges that are visually significant. Experimental results indicate that the method we propose in this paper extracts salient objects effectively and achieves remarkable performance compared to conventional methods. Our method offers benefits in extracting salient objects and generating simple but important edges from images containing natural scene and for providing information to the visually impaired.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.291-292
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• 1998

The purpose of the study was aimed to evaluate the BOLD contrast fMRI in occipital lobe and compare this imaging with metabolite changes based on $^1H$ MRS and MRSI before and after visual stimulation. As a result, the activation map were sucessfully produced by thresholding with minimum cross-correlate value of 0.45. In MRS, NAA/Cr ratio is almost same. however, latate was elevated almost 9 times higher than before activation. Lactate metabolic images were consistent with the BOLD effect map. The BOLD contrast fMRI is not enough to detect the activation area in human brain. so, the other modality was required such as lactate metabolic map.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.3
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• pp.253-259
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• 2014

This study proposes a map-based control method to improve a vehicle's lateral stability, and the performance of the proposed method is compared with that of the conventional model-referenced control method. Model-referenced control uses the sliding mode method to determine the compensated yaw moment; in contrast, the proposed map-based control uses the compensated yaw moment map acquired by vehicle stability analysis. The vehicle stability region is calculated by a topological method based on the trajectory reversal method. The performances of model-referenced control and map-based control are compared under various road conditions and driving inputs. Model-referenced control uses a control input to satisfy the linear reference model, and it generates unnecessary tire lateral forces that may lead to worse performance than an uncontrolled vehicle with step steering input on a road with low friction coefficient. The simulation results show that map-based control provides better stability than model-referenced control.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.1
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• pp.180-188
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• 1995

A modified Kohonen's self-organizing feature map (SOFM) algorithm which has binary reinforcement function and a constant learning rate is proposed. In contrast to the time-varing adaptaion gain of the original Kohonen's SOFM algorithm, the proposed algorithm uses a constant adaptation gain, and adds a binary reinforcement function in order to compensate for the lowered learning ability of SOFM due to the constant learning rate. Since the proposed algorithm does not have the complicated multiplication, it's digital hardware implementation is much easier than that of the original SOFM.