• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.350-352
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• 2013

야외에서 촬영된 영상은 안개나 연무 등에 의한 화질 저하가 나타난다. 이를 해결하기 위하여 안개제거를 위한 여러 장의 영상, 추가정보를 이용하는 안개제거 방법과 한 장의 영상을 이용한 안개제거 방법들이 제안되어왔다. 본 논문에서는 한 장의 영상에서 안개나 연기를 제거하여 가시성이 향상된 영상을 제공하는 방법을 제안한다. 이를 위하여 본 논문에서는 안개영상 모델에 대한 2차원 방정식 풀이를 통해 원 영상에 안개가 어느 정도의 비율로 섞여있는지를 나타내는 전달률(transmission rate)을 계산하고, 계산된 전달률을 이용하여 안개가 제거된 영상을 구한다. 제안된 방식은 기존 방법들과 달리 필터를 사용하지 않고 화소단위의 연산만을 사용하므로 후광효과가 발생하지 않고, 연산량이 매우 적어 실시간 처리가 가능하다.

• Journal of Broadcast Engineering
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• v.21 no.5
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• pp.770-781
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• 2016

As a result of reducing color information and edge information, object distinction in haze image occurs with difficulty. One of the famous defogging algorithm is haze removal by using 'Dark Channel Prior(DCP)', which is used to predict for transmission rate using color information of an image and eliminates haze from the image. But, In case that haze rate is estimated under color information, there is a miscalculated issue which is posed by haze rate and transmission in area with high brightness such as a white object or a light source. In this paper, We deal with a miscalculated issue by correcting from around haze rate, after application of color normalization used by main white part of image haze. Moreover, We calculation improved transmission based on the result of improved haze rate estimation. And then haze image quality is developed through refining transmission.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.814-817
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• 2013

In this paper, we propose a visibility enhancement method using dehazing method in fog situation. The proposed method calculate low bound of the transmission rate that indicate fog rate and transmission that processed power operation in each pixel by the user's control. And we obtain the dehazed image using calculated transmission rate. Proposed method is possible real-time processing, because the method don't cause halo effect and drop operations from filtering by closed form. We can obtain the dehazed image in various fog conditions by user control that strength of removing fog can be adjusted according to the dgree of fog.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1477-1482
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• 2022

Haze is a local weather phenomenon in which very small droplets float in the atmosphere, and the amount and characteristics of haze may vary depending on the region. In particular, these haze reduce visibility, which can cause air traffic interference and vehicle traffic accidents, and degrade the quality of security CCTVs and so on. Therefore, in the past 10 years, research on haze removal has been actively conducted to reduce damage caused by haze. In this study, local haze removal is performed by weight generation using a haziness degree evaluator to adaptively respond to haze-free, homogeneous haze, and non-homogeneous haze cases. And the proposed method improves the limitations of the existing static haze removal method, which assumes that there is haze in the input image and removes the haze. We also demonstrate the superiority of the proposed method through quantitative and qualitative performance evaluations with benchmark algorithms.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.168-176
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• 2014

Detecting moving objects from a video sequence is a fundamental and critical task in video surveillance, traffic monitoring and analysis, and human detection and tracking. It is very difficult to detect moving objects in a video sequence degraded by the environmental factor such as fog. In particular, the color of an object become similar to the neighbor and it reduces the saturation, thus making it very difficult to distinguish the object from the background. For such a reason, it is shown that the performance and reliability of object detection and tracking are poor in the foggy weather. In this paper, we propose a novel method to improve the performance of object detection, combining a haze removal algorithm and a local histogram-based object tracking method. For the quantitative evaluation of the proposed system, information retrieval measurements, recall and precision, are used to quantify how well the performance is improved before and after the haze removal. As a result, the visibility of the image is enhanced and the performance of objects detection is improved.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.11a
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• pp.148-150
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• 2012

외부 환경에 안개가 존재하는 경우, 영상처리의 다양한 알고리즘을 사용하기 어렵다. 이때 안개가 짙은 정도인 전달량을 이용하여 안개를 제거한다. 안개 제거를 위한 대표적인 방법 중 하나인 Dark Channel Prior 알고리즘은 영상의 색 정보를 이용하여 안개의 전달량을 예상한다. 하지만 RGB 전 채널 모두 높은 값을 갖고 있는 영역이, 전달량을 찾는 마스크보다 클 때 전달량을 잘못 예상하게 된다. 본 논문에서는 영상의 edge 정보를 이용하여 영상의 안개가 짙은 정도에 따라 영역을 분할 후 잘못 예상된 전달량을 보정하는 방법을 제안한다. 잘못된 전달량 예상을 통해 색이 왜곡되는 부분을 제거함으로서 기존의 알고리즘과 비교하여 영상 내의 색상이 자연스럽게 안개가 제거된 결과를 얻었다.

• Korean Journal of Weed Science
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• v.15 no.3
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• pp.197-205
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• 1995

The objectives of the present study were to find out 1)the differences in growth of radish under foggy and non-foggy condition, 2)the weed competition between radish and major upland weeds including Echinochloa crus-galli, 3)difference in response of radish to herbicide and weed, and finally 4)the fundamental data for the establishment of radish weed control system under locational foggy regions. The research was carried out by tray in greenhouse equipped with Auto Foggy System(SAE KI RIN Co.) and results were summarized as follows. 1. Plant height and shoot fresh weight of radish cultivars(long skirt, delicious altari, green mascot) were not different at the early growth(8 to 38 days after seeding), but increased at 55 days after seeding under foggy condition. Root fresh weight increased only in green mascot cultivar tinder foggy condition. Chlorophyll contents were higher in all the cultivars of radish under foggy condition. 2. Plant height and shoot fresh weight increased at 0 and 20 days of weed competition under foggy condition. Root fresh weight increased at 0, 20 and 35 days of competition under foggy condition. Above 50 days-competition, there was no difference between foggy and non-foggy condition. 3. Napropamide, alachlor and linuron did not show any differences in plant height and shoot fresh weight between foggy and non-foggy condition. Molinate reduced the root fresh weight at 65 days after seeding tinder foggy condition. 4. No difference in weeding efficacy by any herbicides tested was found tinder foggy condition. Weeding efficacy of Aeschynomene indica was reduced under foggy condition.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.163-170
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• 2013

In general, images of outdoor scenes often contain degradation due to dust, water drop, haze, fog, smoke and so on, as a result they cause the contrast reduction and color fading. Haze removal is not easier problem due to the inherent ambiguity between the haze and the underlying scene. So, we propose a novel method to solve single scene dehazing problem using the region segmentation based on graph algorithm that has used a gradient value as a cost function. We segment the scene into different regions according to depth-related information and then estimate the global atmospheric light. The medium transmission can be directly estimated by the threshold function of graph-based segmentation algorithm. After estimating the medium transmission, we can restore the haze-free scene. We evaluated the degree of the visibility restoration between the proposed method and the existing methods by calculating the gradient of the edge between the restored scene and the original scene. Results on a variety of outdoor haze scene demonstrated the powerful haze removal and enhanced image quality of the proposed method.

• Journal of Broadcast Engineering
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• v.20 no.5
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• pp.738-747
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• 2015

It is difficult to use a recognition algorithm of an image in a foggy environment because the color and edge information is removed. One of the famous defogging algorithm is haze removal by using 'Dark Channel Prior(DCP)' which is used to predict for transmission rate using color information of an image and eliminates fog from the image. However, in case that the image has factors such as sunset or yellow dust, there is overemphasized problem on the color of certain channel after haze removal. Furthermore, in case that the image includes an object containing high RGB channel, the transmission related to this area causes a misestimated issue. In this paper, we purpose an enhanced fog elimination algorithm by using improved color normalization and haze rate revision which correct mis-estimation haze area on the basis of color information and edge information of an image. By eliminating the color distortion, we can obtain more natural clean image from the haze image.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.12
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• pp.571-576
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• 2015

Image dehazing has been extensively studied, but the performance evaluation method for dehazing techniques has not attracted significant interest. This paper surveys many existing performance evaluation methods of image dehazing. In order to analyze the reliability of the evaluation methods, synthetic hazy images are first reconstructed using the ground-truth color and depth image pairs, and the dehazed images are then compared with the original haze-free images. Meanwhile we also evaluate dehazing algorithms not by the dehazed images' quality but by the performance of computer vision algorithms before/after applying image dehazing. All the aforementioned evaluation methods are analyzed and compared, and research direction for improving the existing methods is discussed.