• Information Display
• /
• v.20 no.3
• /
• pp.3-9
• /
• 2019

본 논문에서는 HDR imaging 기술의 기본 원리와 전반적인 내용에 대해서 살펴보았다. 특히 최근 많은 관심을 받고 있는 딥러닝 기술에 대한 소개와 HDR imaging 기술에 어떤 형태로 적용되고 있는지에 대한 내용 및 최근 동향에 대해서도 함께 살펴보았다. HDR imaging 기술은 기존 디스플레이 대비 높은 인지 화질을 제공해주기 때문에 현재 많은 관심을 받고 있는 기술이며, 디스플레이 패널 기술 발전과 함께 지속적으로 연구되어야 하는 기술이다. 이와 관련해서 현재 많은 연구 기관 등에 대해서 관련 기술에 대해서 연구하고 있지만, 아직 많은 부분에 있어서 해결되어야 하겠다. 특히 궁극적으로 인간의 시각 특성을 고려한 영상 출력을 위해서는 디스플레이 기술 발전과 함께 알고리즘 측면에서 많은 연구가필요하겠다. 따라서 이러한 HDR imaging 기술을 포함한 다양한 알고리즘 개발을 통해서 현재보다 높은 수준의 실감형 디스플레이 기술 개발이 이루어질 것으로 기대된다.

• Journal of the Semiconductor & Display Technology
• /
• v.16 no.3
• /
• pp.82-86
• /
• 2017

High dynamic range (HDR) imaging offers a radically approach of representing colors in digital images. Instead of using the range of colors produced by given devices, HDR imaging method manipulates and stores all colors and brightness levels visible to the human eye. To faithfully represent, store and then reproduce all these effects, the original scene must be stored and treated using high fidelity HDR techniques. Then, tone mapping is required to accommodate HDR image to low dynamic range (LDR) devices, and tone mapping operation of HDR image for realistic display is commonly researched. However, color visualization for analyzing scene luminance in HDR imaging has less attention from researches. This paper presents and implements a method for reproduction and visualization of the false color in HDR images. We produce a color visualization framework with several mapping functions, and evaluate their effectiveness by using RMAE and SNR with commonly used HDR image data. Experiment reveals that the sigmodal mapping function shows better performance in the false color visualization, compared to other methods.

• Journal of Broadcast Engineering
• /
• v.23 no.3
• /
• pp.369-382
• /
• 2018

We propose a single-shot high dynamic range (HDR) imaging algorithm using a deep convolutional neural network (CNN) for row-wise varying exposures in a single image. The proposed algorithm restores missing information resulting from under- and/or over-exposed pixels in an input image and reconstructs the raw radiance map. The main contribution of this work is the development of a loss function for the CNN employing the human visual system (HVS) properties. Then, the HDR image is obtained by applying a demosaicing algorithm. Experimental results demonstrate that the proposed algorithm provides higher-quality HDR images than conventional algorithms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2015.10a
• /
• pp.705-708
• /
• 2015

High dynamic range (HDR) imaging is a techniques used in imaging to reproduce a greater dynamic range of luminosity than is possible with standard digital imaging. Tone mapping of HDR images for realistic display is commonly studied. However, scientific visualization of HDR image for analysis of scene luminance has much less attention. In this paper, we present and implement a simple approach for the reproduction and visualization of color information in HDR images. We attempt several simple color visualizing functions, and estimate their effectiveness through the evaluation factors with common HDR images.

• Journal of Broadcast Engineering
• /
• v.23 no.5
• /
• pp.714-717
• /
• 2018

This paper presents a method of HDR imaging with adaptive saturation compensation for brightness change. The saturation of HDR images were lighten on dark region because conventional HDR methods have focused on brightness change. Therefore, the proposed HDR method compensates saturation adaptively according to brightness change. For experiments of several images, the proposed algorithm is superior to conventional HDR methods qualitatively and quantitatively in terms of color saturation.

• Journal of The Korean Digital Architecture Interior Association
• /
• v.12 no.3
• /
• pp.81-89
• /
• 2012

Luminance is the most important quantity in lighting design and illuminating engineering. There are three methods for measuring luminance; using a conventional luminance meter, through the illuminance measurement and subsequent calculations and using digital imaging photometer. Recently, HDRI(High Dynamic Range Imaging) technique introduces a new method of capturing luminance values in a lighting environment. The radiance maps from HDRI are commonly used as visual environment maps for lighting analysis applications. For the HDRI, HDR software is needed to create HDR image. Currently, there is number of HDR software available. The purpose of this paper is to investigate whether a luminance map can be accurately captured by the various types of HDR software which include HDR Shop and Photoshop. To accomplish this goal a set of experiments was conducted. In order to assess the luminance values of the HDR image from HDR software, the values had to be compared to the ones obtained with conventional methods of luminance measurement.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.1
• /
• pp.111-120
• /
• 2015

HDR(High dynamic range) imaging is a technique to represent a dynamic range of real world. Exposure fusion is a method to obtain a pseudo-HDR image and it directly fuses multi-exposure images instead of generating the true-HDR image. However, it results ghost artifacts while fusing the multi-exposure images with moving objects. To solve this drawback, temporal consistency assessment is proposed to remove moving objects. Firstly, multi-level threshold bitmap and brightness bitmap are proposed. In addition, hue-angle constancy map between multi-exposure images is proposed for compensating a bitmap. Then, two bitmaps are combined as a temporal weight map. Spatial domain image quality assessment is used to generate a spatial weight map. Finally, two weight maps are applied at each multi-exposure image and combined to get the pseudo-HDR image. In experiments, the proposed method reduces ghost artifacts more than previous methods. The quantitative ghost-free evaluation of the proposed method is also less than others.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.28 no.7
• /
• pp.26-33
• /
• 2014

The purpose of this study is to evaluate the accuracy of luminance maps generated from five types of HDRI builder(High Dynamic Ranging Image builder) which include Photosphere, Bracket, Picturenaut, Luminance HDR and Photoshop. To accomplish this goal a set of experiments was conducted. In order to assess the luminance values of the HDR image from HDR image builder, the values had to be compared to the ones obtained from imaging photometer. After comparing measured luminance data using imaging photometer with those retrieved from the HDR images, Photosphere error rate estimated at 3% below.

• Journal of the Korea Computer Graphics Society
• /
• v.29 no.3
• /
• pp.13-19
• /
• 2023

카메라 센서의 한계로 인하여 촬영 장면에 따라 한 번의 촬영으로 모든 영역의 밝기가 적절하게 촬영되지 않는 경우가 존재한다. 이러한 센서의 한계는 하이 다이나믹 레인지 이미징 기술을 통해서 극복이 가능하다. 한 장면을 다양한 노출 설정으로 여러 번 촬영하는 브라케팅은 움직이는 피사체를 찍기에 적절하지 않으며 촬영 시간이 길다는 단점이 있다. 본 연구는 한 번의 촬영으로 서로 다른 노출의 이미지를 얻을 수 있는 소형 라이트필드 카메라를 제안한다. 라이트필드 카메라는 대표적으로 두 가지 형태가 있는데, 첫 번째는 여러 대의 카메라를 어레이로 배치한 라이트필드 카메라 시스템이며, 두 번째는 대물렌즈 뒤에 마이크로 렌즈 어레이를 배치한 카메라이다. 본 연구에서 제작된 초박형 라이트필드 카메라는 센서 위에 마이크로 렌즈어레이가 부착되어있는 형태의 카메라로 각 렌즈 조리개 크기를 다르게 설계하여 한 번의 촬영으로 다른 노출의 촬영 결과를 얻을 수 있게 설계되었다. 촬영된 단일 영상들을 전처리 하여 이미지 품질을 높인 이후, HDR 알고리즘을 통해 각 단일 이미지들보다 다이나믹 레인지가 넓은 이미지를 획득하도록 구현하였다. 또한 노출 시간을 기준으로 설계된 식을 수정하여 조리개값에 따라 다른 가중치를 둘 수 있도록 바꾸었고, 이를 통해 단 한 번의 촬영을 통한 HDR 이미징을 구현하였다.

• Journal of Broadcast Engineering
• /
• v.16 no.2
• /
• pp.247-257
• /
• 2011

In this paper, we propose a scene adaptive method to obtain two LDR images with proper shutter speeds which capture the irradiance of scene effectively. The proposed method adaptively selects two shutter speeds across the video frame even when the illumination varies continuously. For the performance evaluation, we compute the PNSR to the ground truth which is obtained by the state-of-the-art HDR imaging method. It shows that the proposed method is able to select approximately optimal shutter speeds while avoiding the exhaustive search of every possible pair of shutter speeds.