• Journal of Korea Multimedia Society
• /
• v.6 no.6
• /
• pp.977-984
• /
• 2003

In this paper, we propose an image enhancement algorithm for panoramic infrared image. This method divides a panoramic infrared image into disjoint subimages and performs the contrast stretch for subimages using statistical characteristics of each subimage. But these cause blocking artifact in boundary regions of neighboring subimages which different to the statistical characteristic. To remove blocking artifact, we perform the contrast stretch for subimage's boundary regions using statistical characteristics of horizontally neighboring subimages. Experimental results show that the proposed method effectively improves their appearance to human viewers.

• Journal of Information Processing Systems
• /
• v.14 no.6
• /
• pp.1405-1419
• /
• 2018

An image fusion method is proposed on the basis of depth model segmentation to overcome the shortcomings of noise interference and artifacts caused by infrared and visible image fusion. Firstly, the deep Boltzmann machine is used to perform the priori learning of infrared and visible target and background contour, and the depth segmentation model of the contour is constructed. The Split Bregman iterative algorithm is employed to gain the optimal energy segmentation of infrared and visible image contours. Then, the nonsubsampled contourlet transform (NSCT) transform is taken to decompose the source image, and the corresponding rules are used to integrate the coefficients in the light of the segmented background contour. Finally, the NSCT inverse transform is used to reconstruct the fused image. The simulation results of MATLAB indicates that the proposed algorithm can obtain the fusion result of both target and background contours effectively, with a high contrast and noise suppression in subjective evaluation as well as great merits in objective quantitative indicators.

• Journal of Sensor Science and Technology
• /
• v.9 no.1
• /
• pp.44-50
• /
• 2000

Every object emits some energy from its surface. The emission energy forms surface heat distribution which we can capture by using an infrared thermal imager. The infrared thermal image may include valuable information regarding to the subsurface anomaly of the object. Since a thermal image reflects surface clutter and subsurface anomaly, we have difficulty in extracting the information on the subsurface anomaly only with thermal images taken under a wavelength. Thus, we use visible wavelength images of the object surface to remove exterior clutter. We, therefore in this paper, visualize the infrared image for overlaying it with a visible wavelength image. First, we make an interpolated image from two ordinary images taken from both sides of an infrared sensor. Next, we overlay the intermediate image with an infrared image taken from the infrared camera. The technique suggested in this paper can be utilized for analyzing the infrared images on non-destructive inspection against disaster and for safety.

• Korean Journal of Optics and Photonics
• /
• v.31 no.6
• /
• pp.314-320
• /
• 2020

The optics used in an infrared imaging system has a strong refractive-index change according to temperature, so an autofocus control function is essential for a military infrared imaging system with a wide operating-temperature range. In this study, we design a triple-magnification infrared imaging system, and to compensate for the change in refractive index according to temperature we measure the change in the lens focus according to temperature. The autofocus control function was implemented by using the measured movement amount, and we could obtain an image with satisfactory resolution performance over a wide range of operating temperatures.

• Journal of the Korean Physical Society
• /
• v.73 no.11
• /
• pp.1644-1649
• /
• 2018

Aiming at infrared thermal images with different buried depth defects, we study a variety of image segmentation algorithms based on the threshold to develop global search ability and the ability to find the defect area accurately. Firstly, the iterative thresholding method, the maximum entropy method, the minimum error method, the Ostu method and the minimum skewness method are applied to image segmentation of the same infrared thermal image. The study shows that the maximum entropy method and the minimum error method have strong global search capability and can simultaneously extract defects at different depths. However none of these five methods can accurately calculate the defect area at different depths. In order to solve this problem, we put forward a strategy of "divide and conquer". The infrared thermal image is divided into several local thermal maps, with each map containing only one defect, and the defect area is calculated after local image processing of the different buried defects one by one. The results show that, under the "divide and conquer" strategy, the iterative threshold method and the Ostu method have the advantage of high precision and can accurately extract the area of different defects at different depths, with an error of less than 5%.

• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.578-578
• /
• 2002

Thermal infrared imaging is a highly promising technology for condition monitoring and predictive maintenance of electronic, electrical and mechanical elements in nuclear power plants. However, conventional low-cost infrared imaging systems suffer from poor spatial resolution compared to commercial CCD cameras. This paper describes an approach to enhance inspection performances for calandria reactor area of Wolsung nuclear power plant through the technique of superimposing thermal infrared image into real CCD image. In the occurrence of thermal abnormalities on observation points and areas of calandria reactor area, unusual hot image taken from thermal infrared camera is mapped upon real CCD image. The performance of the technique has been evaluated in the experiment carried out at Wolsung nuclear power plant in the overhaul period. The results show that localizations of thermal abnormalities on calandria reactor face can be estimated accurately.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.10
• /
• pp.5006-5022
• /
• 2017

Effect and robust detection of targets in infrared images has crucial meaning for many applications, such as infrared guidance, early warning, and video surveillance. However, it is not an easy task due to the special characteristics of the infrared images, in which the background clutters are severe and the targets are weak. The recent literature demonstrates that sparse representation can help handle the detection problem, however, the detection performance should be improved. To this end, in this text, a hybrid method based on local sparse representation and contrast is proposed, which can effectively and robustly detect the infrared targets. First, a residual image is calculated based on local sparse representation for the original image, in which the target can be effectively highlighted. Then, a local contrast based method is adopted to compute the target prediction image, in which the background clutters can be highly suppressed. Subsequently, the residual image and the target prediction image are combined together adaptively so as to accurately and robustly locate the targets. Based on a set of comprehensive experiments, our algorithm has demonstrated better performance than other existing alternatives.

• Journal of the Korean Solar Energy Society
• /
• v.33 no.5
• /
• pp.51-59
• /
• 2013

It is usual to evaluate the performance of the cool roof by measuring in-site rooftop temperature using thermal infra-red camera. The principal advantage of rooftop thermal infrared image acquired in oblique vantage point of super high-rise building as a remote sensor is to provide, in a cost-effective manner, area-wide information required for a scattered rooftop target with different colors, utilizing wide view angle and multi-temporal data coverage. This research idea was formulated by incorporating the concept of traditional remote sensing into rooftop temperature monitoring. Correlations between infrared image of super high-rise building and in-situ data were investigated to compare rooftop surface temperature for a total of four different rooftop locations. The results of the correlations analyses indicate that the rooftop surface temperature by the infrared images of super high-rise building alone could be explained yielding $R^2$ values of 0.951. The visible permanent record of the oblique thermal infra-red image was quite useful in better understanding the nature and extent of rooftop color that occurs in sampling points. This thermal infrared image acquired in oblique vantage point of super high-rise made it possible to identify area wide patterns of rooftop temperature change subject to many different colors, which cannot be acquired by traditional in-site field sampling. The infrared image of super high-rise building breaks down the usual concept of field sampling established as a conventional cool roof performance evaluation technique.

• 전자공학회논문지 IE
• /
• v.48 no.2
• /
• pp.32-39
• /
• 2011

The output image of the uncooled thermal infrared camera is difficult the identification of target because of the limited dynamic range and the various noises. Retinex algorithm based on the theory of the human visual perception is known to be effective contrast enhancement technique. However, the image quality is insufficient when it is adopted to the narrow dynamic range image as the infrared image. In this paper, we propose the revised retinex algorithm to enhance the contrast of the infrared image. To improve the contrast enhancement performance, we designed the new dynamic range compression function instead of log function. To reduce the noise and compensate the loss of edge, we added the contrast compensation procedure in the MSR image generation process. According to the output picture comparing and numerical analysis, the proposed algorithm shows the better contrast enhancement performance and the more suitable method for the infrared image enhancement.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.10
• /
• pp.5039-5055
• /
• 2018

The quality of natural outdoor images captured by visible camera sensors is usually degraded by the haze present in the atmosphere. In this paper, a fast image dehazing method based on visible image and near-infrared fusion is proposed. In the proposed method, a visible and a near-infrared (NIR) image of the same scene is fused based on the dual-tree complex wavelet transform (DT-CWT) to generate a dehazed color image. The color of the fusion image is regulated through haze concentration estimated by dark channel prior (DCP). The experiment results demonstrate that the proposed method outperforms the conventional dehazing methods and effectively solves the color distortion problem in the dehazing process.