• Journal of the Korea Computer Graphics Society
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• v.27 no.3
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• pp.31-42
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• 2021

We propose a deep learning-based method that can estimate an appropriate lighting of both indoor and outdoor images. The method consists of two networks: Crop-to-PanoLDR network and LDR-to-HDR network. The Crop-to-PanoLDR network predicts a low dynamic range (LDR) environment map from a single partially observed normal field of view image, and the LDR-to-HDR network transforms the predicted LDR image into a high dynamic range (HDR) environment map which includes the high intensity light information. The HDR environment map generated through this process is applied when rendering virtual objects in the given image. The direction of the estimated light along with ambient light illuminating the virtual object is examined to verify the effectiveness of the proposed method. For this, the results from our method are compared with those from the methods that consider either indoor images or outdoor images only. In addition, the effect of the loss function, which plays the role of classifying images into indoor or outdoor was tested and verified. Finally, a user test was conducted to compare the quality of the environment map created in this study with those created by existing research.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.837-847
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• 2016

Tone mapping for High Dynamic Range(HDR) image provides matching human visual perception between real world scene and displayable devices. Recently, a tone mapping algorithm based on localized gamma correction is proposed. This algorithm is using human visual properties of contrast and colorfulness with background intensity, generating a weight map for gamma correction. However, this method have limitations of controlling enhancement region as well as generating halo artifacts caused by the weight map construction. To overcome aforementioned limitations, proposed algorithm in this paper modifies previous weight map, considering base layer intensity of input luminance channel. By determining enhancement region locally and globally based on base layer intensity, gamma values are corrected accordingly. Therefore, proposed algorithm selectively enhances local brightness and controls strength of edges. Subjective evaluation using z-score shows that our proposed algorithm outperforms the conventional methods.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.06a
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• pp.211-214
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• 2016

본 논문에서는 하나의 넓은 동적 영역(High Dynamic Range: HDR)을 갖는 이미지를 Earth Mover's Distance(EMD)값을 이용한 이미지 분할 기법을 적용한 유사 지역 그룹화를 통해, 각 그룹별로 톤 매핑을 수행하는 기법을 제안하고자 한다. 기존의 EMD 값을 통한 이미지 분할 알고리듬은 이미지 내의 같은 그룹으로 분류된 지역에서 휘도(luminance)의 변화가 클 때 후광 현상(halo artifact)이 발생하는 문제점을 보였다. 본 논문에서는 기존의 알고리듬으로 분할된 이미지를 처리할 때 휘도 변화량(gradient)의 정보를 활용하여 후광 현상 제거함으로써 주관적 화질을 향상시켰다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.06a
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• pp.55-58
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• 2017

본 논문에서는 넓은 동적 영역(High Dynamic Range: HDR) 이미지에 지역 엣지 보존 필터를 적용한 개선된 다중 스케일 톤 매핑 기법을 제안하고자 한다. 기존 알고리듬의 다중 스케일 분해 과정에서는 과도하게 많은 정보를 보존하여 결과 이미지가 비현실적으로 표현되고 일부 테스트 이미지에서는 화소 값 변화량이 큰 엣지 영역에서 후광 효과가 발생하는 단점이 있다. 본 논문에서는 기존 알고리듬의 다중 스케일 분해 과정을 개선하여 엣지를 적절히 보존함으로써 후광 효과를 제거함과 동시에 주관적 화질을 향상시켰다.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.143-146
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• 2008

Dynamic range of LCD panel can be dramatically improved by adaptive dimming technique. Adaptive control of LED backlight by input signal can reduce the light leakage of LCD panel and achieve high contrast ratio. An algorithm is proposed to distinguish the input signal and get proper luminance level. For lower cost of LCD panel, white light LED is used to accomplish 2D dimming and get better image performance of LCD.

• Journal of the Korean Society of Radiology
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• v.7 no.1
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• pp.63-69
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• 2013

Comparing with film-screen system, flat-panel detector has extensive dynamic range. Focusing flat-panel detector, whole body human phantom PBU-50 (Kyoto, kagaku, Japan) was used to perform comparative study of the estimate of image quality and exposure dose. the exposure condition was 81kV and 20mAs, which is used for Abdomen supine exam in clinical area. As a result of the kV change of the interpreted medical image which has over 30dB of PSNR value, the value of DAP shows the difference of 19.6 times. Moreover, the result of comparing kV change with effective dose of ICRP 103 shows that stochastic effect was increased by over exposure. Therefore, it is significantly necessary that digital radiation technical chart will be used to obtain high quality image and make the standard of dose by educating radio-technologist continually.

• Journal of Korea Game Society
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• v.7 no.4
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• pp.53-62
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• 2007

Although radiosity can represent diffuse reflections of the object surfaces by modeling energy exchange in 3D space, there are some restrictions for real-time applications because of its computation loads. Therefore, GPU(Graphics Processing Unit) based radiosity algorithms have been presented actively to improve its rendering performance. We implement the progressive refinement radiosity on GPU by G. Coombe in 3D scene that is constructed with HDR(High Dynamic Range) radiance map. This radiosity method can generate a photo-realistic rendering image in 3D space, where the synthetic objects were illuminated by the environmental light sources. In the simulation results, the rendering performance is analyzed according to the resolution of the texel in the environmental map and mipmaping. In addition, we compare the rendering results by our method with those by the incremental radiosity.

• Journal of Korea Multimedia Society
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• v.16 no.3
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• pp.281-289
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• 2013

The iCAM06 has been used as an image appearance model for HDR image rendering. The iCAM06 goes through the color space conversions and scale conversions of the several steps to present HDR images. The dynamic range of an HDR image needs to be mapped on the range of output devices, which is called the tone mapping. However, tone compression process of the iCAM06 causes color distortion because of color-clipping and cross-stimulus. Therefore, we proposed that a color correction method in IPT space which compensates the color distortion in tone compression process. Through the experimental results, we conformed that proposed color correction method had better performance than the iCAM06 and enhanced models.

• Journal of Korea Multimedia Society
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• v.24 no.8
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• pp.1059-1067
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• 2021

In this paper, a HDR algorithm for a single image is proposed using the exposure fusion, that adaptively calculates gamma correction coefficients according to the image distribution. Since typical HDR methods should use at least three images with different exposure values at the same scene, the main problem was that they could not be applied at the single shot image. Thus, HDR enhancements based on a single image using tone mapping and histogram modifications were recently presented, but these created some location-specific noises due to improper corrections. Therefore, the proposed algorithm calculates proper gamma coefficients according to the distribution of the input image and generates different exposure images which are corrected by the dark and the bright region stretching. A HDR image reproduction controlling exposure fusion weights among the gamma corrected and the original pixels is presented. As the result, the proposed algorithm can reduce certain noises at both the flat and the edge areas and obtain subjectively superior image quality to that of conventional methods.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.11
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• pp.73-81
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• 2016

In general, infrared images have less sharpness and image details than visible images. So, the prior image upscaling methods are not effective in the infrared images. In order to solve this problem, this paper proposes an algorithm which initially up-scales an input infrared (IR) image by using adaptive dynamic range encoding (ADRC)-based super-resolution (SR) method, and then fuses the result with the corresponding visible images. The proposed algorithm consists of a up-scaling phase and a fusion phase. First, an input IR image is up-scaled by the proposed ADRC-based SR algorithm. In the dictionary learning stage of this up-scaling phase, so-called 'pre-emphasis' processing is applied to training-purpose high-resolution images, hence better sharpness is achieved. In the following fusion phase, high-frequency information is extracted from the visible image corresponding to the IR image, and it is adaptively weighted according to the complexity of the IR image. Finally, a up-scaled IR image is obtained by adding the processed high-frequency information to the up-scaled IR image. The experimental results show than the proposed algorithm provides better results than the state-of-the-art SR, i.e., anchored neighborhood regression (A+) algorithm. For example, in terms of just noticeable blur (JNB), the proposed algorithm shows higher value by 0.2184 than the A+. Also, the proposed algorithm outperforms the previous works even in terms of subjective visual quality.