• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.171-174
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• 2003

This paper is a study on the 3D infrared image enhancement with Stereoscopic algorithm on still infrared image. The adapted stereo method is that the depth is extracted by comparison with right-left image, and the enhanced 3D infrared image by matching based on feature is realized. As the result of experiment this method forced the more smooth edge lines of 3D infrared images.

• Proceedings of the KSRS Conference
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• v.2
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• pp.736-739
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• 2006

While hyperspectral data are very rich in information, their processing poses several challenges such as computational requirements, noise removal and relevant information extraction. In this paper, the application of advanced scale-space filtering to selected hyperspectral bands was investigated. In particular, a pre-processing tool, consisting of anisotropic diffusion and morphological leveling filtering, has been developed, aiming to an edge-preserving smoothing and simplification of hyperspectral data, procedures which are of fundamental importance during feature extraction and object detection. Two scale space parameters define the extent of image smoothing (anisotropic diffusion iterations) and image simplification (scale of morphological levelings). Experimental results demonstrated the effectiveness of the developed scale space filtering for the enhancement and smoothing of hyperspectral remote sensing data and their advantage against watershed over-segmentation problems and edge detection.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.3
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• pp.577-581
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• 2003

The 3D infrared image enhancement with Stereoscopic algorithm on still infrared image is presented. The adapted stereoscopic method is that the depth is extracted by comparison with right-left image, and the enhanced 3D infrared image by matching based on feature is realized. As the result of experiment this method forces a 3D infrared image by the edge lines to be more smooth.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.222-224
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• 2009

This paper presents an algorithm that extracts road lane's specific information by using HSI color information and performance enhancement of lane detection base on vision processing of drive assist. As a preprocessing for high speed lane detection, the optimal extraction of region of interest for lane boundary(ROI-LB) can be processed to reduction of detection region in which high speed processing is enabled and it also increases reliabilities by deleting edges those are misrecognized. Road lane is extracted with simultaneous processing of noise reduction and edge enhancement using the Laplacian filter, the reliability of feature extraction can be increased for various road lane patterns. Since noise can be removed by using saturation and brightness of HSI color model. Also it searches for the road lane's color information and extracts characteristics. The real road experimental results are presented to evaluate the effectiveness of the proposed method.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.2
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• pp.78-86
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• 1993

A nonlinear method for directional information processing is introduced, along with an application of directional feature enhancement. In this method, an input is convolved with a 2-D ong, norrow kernel, which is rotated through 360 degree, continuously or discretely in a large number of steps. An output is given by some function of the convolution results. Linear features that are aligned with the kernel are enhanced, otherwise, removed or suppressed. The method presented is insensitive to variation in the dimension of linear features to be processed and preserves a good enhancement capability even for an image characterized by low contrast and spatially varying brightness in noisy backgroung. Effects of the kernel legnth and width on the performance are discussed. A possible hybrid optical-electronic implementation is also discussed.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.361-362
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• 2007

We propose a contrast-controlled feature detection approach for steel radiograph image. X-ray images are low contrast, dark and high noise image. So, It is not simple to detect defects directly in automated radiography inspection system. Contrast enhancement, histogram equalization and median filter are the most frequently used techniques to enhance the X-ray images. In this paper, the adaptive control method based on contrast limited histogram equalization is compared with several histogram techniques. Through comparative analysis, CLAHE(contrast controlled adaptive histogram equalization) can enhance detection of defects better.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.3
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• pp.101-113
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• 2015

The purpose of this study is increasing ventilation network usability for urban green space planning by enhancing its practicality and detail. A ventilation network feature extraction technique using roughness length($z_0$) was proposed. Continuously surfaced DZoMs generated from $z_0$(cadastral unit) using three interpolations(IDW, Spline, and Kriging) were compared to choose the most suitable interpolation method. Ventilation network features were extracted using the most suitable interpolation technique and studied with land cover and land surface temperature by spatial overlay comparison. Results show Kriging is most suitable for DZoM and feature extraction in comparison with IDW and Spline. Kriging based features are well fit to the land surface temperature(Landsat-7 ETM+) on summer and winter nights. Noteworthy is that the produced ventilation network appears to mitigate urban heat loads at night. The practical use of proposed ventilation network features are highly expected for urban green space planning, though strict validation and enhancement should follow. (1) $z_0$ enhancement, (2) additional ventilation network interpretation and editing, (3) linking disconnected ventilation network features, and (4) associated dataset enhancement with data integrity should technically preceded to enhance the applicability of a ventilation network for green space planning. The study domain will be expanded to the Seoul metropolitan area to apply the proposed ventilation network to green space planning practice.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.12
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• pp.59-66
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• 2006

To understand the role of helical geometry on the regression rate enhancement, two competing underlying mechanisms such as turbulence enhancement and swirling motion production were studied by numerical calculations. Experimental results showed that the enhancement of heat transfer rate has the very close relation to the increase in regression rate even though the percentage of increase in heat transfer rate is different from that in regression rate. This discrepancy is presumably due to the change of turbulent flow feature caused by so-called "blowing mass flux" from the fuel surface. In this regard, the results of RANS calculation show that the blowing velocity is responsible for the reduction of the swirl generation and the increase in the turbulent kinetic energy. And the dominancy of one of the mechanisms causes the increase in the regression rate. Meanwhile, the increase in turbulent kinetic energy due to the mixing of blowing flow and free stream flow does not contribute for the enhancement of the heat transfer rate to the surface because the blowing flow pushes boundary layer away from the solid surface.

• The Journal of the Acoustical Society of Korea
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• v.42 no.2
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• pp.94-101
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• 2023

A deep neural network composed of encoders and decoders, such as U-Net, used for speech enhancement, concatenates the encoder to the decoder through skip-connection. Skip-connection helps reconstruct the enhanced spectrum and complement the lost information. The features of the encoder and the decoder connected by the skip-connection are incompatible with each other. In this paper, for complex-valued spectrum based speech enhancement, Self-Attention (SA) method is applied to skip-connection to transform the feature of encoder to be compatible with the features of decoder. SA is a technique in which when generating an output sequence in a sequence-to-sequence tasks the weighted average of input is used to put attention on subsets of input, showing that noise can be effectively eliminated by being applied in speech enhancement. The three models using encoder and decoder features to apply SA to skip-connection are studied. As experimental results using TIMIT database, the proposed methods show improvements in all evaluation metrics compared to the Deep Complex U-Net (DCUNET) with skip-connection only.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.1
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• pp.36-41
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• 2015

This paper is proposed a wavelet-based MCDT(Mask Coefficient Differential and Threshold) method of image registration of Multi-images contaminated with visible image and infrared image. The method for ensure reliability of the image registration is to the increase statistical corelation as getting the common feature points between two images. The method of threshold the wavelet coefficients using derivatives of the wavelet coefficients of the detail subbands was proposed to effectively registration images with distortion. And it can define that the edge map. Particularly, in order to increase statistical corelation the method of the normalized mutual information. as similarity measure common feature between two images was selected. The proposed method is totally verified by comparing with the several other multi-image and the proposed image registration.