• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8B
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• pp.1480-1489
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• 1999

In this paper, we propose a new post-processing method which can solve a problem of MSDS(Mean Squared Difference of Slope) method. Using that method the blocking artifacts can significantly be reduced without any restriction, which is a major drawback of block-based DCT compression method. In this approach, the OSLD(Overlapped Sub-Laplacian Distribution) of dequantized block boundary pixel difference values is defined and used to categorize each block of an image into one of four types. Those types are also classified into one of two classes: an edge and a non-edge classes. A slope across the block boundary is used to quantify discontinuity of the image. If an absolute estimated quantization error value of a DCT coefficient is greater than the corresponding quantization step size, it is saturated to the step size in the edge class. The proposed post-processing method can improve not only the PSNR value up to 0.1~O.3 dB but visual quality without any constraints determined by ad-hoc manner.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.2C
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• pp.113-123
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• 2007

In Ubiquitous communication environment, various conversions of images are essential, and most digital images are compressed by standard methods such as the Joint Photographic Expert Group (JPEG) and Motion Picture Expert Group (MPEG) which are based on the discrete cosine transform (DCT). In this paper, various image resizing algorithms in the DCT domain are analyzed, and a new image resizing algorithm, which shows superior performance compared with the conventional methods, is proposed. For arbitrary-ratio image resizing in the DCT domain, several blocks of $8{\times}8$ DCT coefficients are converted into one block using the conversion formula in the proposed algorithm, and the size of the inverse discrete cosine transform (IDCT) is decided optimally. The performance is analyzed by comparing the peak signal to noise ratio (PSNR) between original images and converted images. The performance of the proposed algorithm is better than that of the conventional algorithm, since the correlation of pixels in images is utilized more efficiently.

• The KIPS Transactions:PartB
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• v.18B no.3
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• pp.139-146
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• 2011

The color correction is the important process of influencing on the picture quality of the 3D stereoscopic images. Existing colorcorrecting methods handle the processing intensifying a correspondence among a left and right image using a histogram based on any one side. In case of color correction based on a histogram, it is difficult to correct tone of image, because the color temperature is not converted enough. And in this paper, the color temperature correction and color consistency correction is proposed without using histogram. The proposed color correction method by color temperature gives 3 in CIE-${\Delta}E$ for each pixel on the images captured with same illuminants and the conventional gives similar results. For color consistency, the proposed gives 9 in CIE-${\Delta}E$ on the images captured with different illuminants while the conventional gives 18. The proposed method shows better results than the conventional in color consistency processing.

• The Journal of the Korea Contents Association
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• v.15 no.10
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• pp.1-9
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• 2015

In this paper, a study on facial movements are analyzed in terms of opposite emotion stimuli by image processing of Kinect facial image. To induce two opposite emotion pairs such as "Sad - Excitement"and "Contentment - Angry" which are oppositely positioned onto Russell's 2D emotion model, both visual and auditory stimuli are given to subjects. Firstly, 31 main points are chosen among 121 facial feature points of active appearance model obtained from Kinect Face Tracking SDK. Then, pixel changes around 31 main points are analyzed. In here, local minimum shift matching method is used in order to solve a problem of non-linear facial movement. At results, right and left side facial movements were occurred in cases of "Sad" and "Excitement" emotions, respectively. Left side facial movement was comparatively more occurred in case of "Contentment" emotion. In contrast, both left and right side movements were occurred in case of "Angry" emotion.

• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.117-124
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• 2008

This paper introduces a novel approach for automated mapping of a map feature that is vinyl green house in high spatial resolution imagery Some map features have their unique spatial patterns. These patterns are normally detected in high spatial resolution remotely sensed data by human recognition system. When spatial patterns can be applied to map feature identification, it will improve image classification accuracy and will be contributed a lot to feature identification. In this study, an automated feature identification approach using spatial aucorrelation is developed, specifically for the vinyl green house that has distinctive spatial pattern in its array. The algorithm aimed to develop the method without any human intervention such as digitizing. The method can investigate the characteristics of repeated spatial pattern of vinyl green house. The repeated spatial pattern comes from the orderly array of vinyl green house. For this, object-based approaches are essential because the pattern is recognized when the shapes that are consists of the groups of pixels are involved. The experimental result shows very effective vinyl house extraction. The targeted three vinyl green houses were exactly identified in the IKONOS image for a part of Jeju area.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.133-133
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• 2019

하천의 하상재료는 전반적인 하천 계획 및 정비 등의 기초자료이다. 특히 하천의 하상재료 조사는 하천의 조도계수 산정, 하천의 유사이송 특성 분석 및 하천 서식처 등의 하천환경 조사를 위하여 수행한다. 지금까지의 하천 하상재료 조사는 사람이 직접 하상토를 채취하거나 사진을 이용하여 대략적인 스케치를 통해 진행하다보니 자료의 품질에 대한 신뢰도가 떨어지고, 사람이 직접조사를 해야 하기 때문에 비용이 많이 필요하여 몇 개 지점을 대상으로 하상재료 조사를 수행해야 하는 등의 한계를 가지고 있다. 따라서 하천 환경 평가를 위한 하상재료 조사를 위해서는 좀 더 체계적이고 과학적인 기술 개발이 요구된다. 특히 물속의 하천 하상재료를 조사하는 것은 육안 또는 카메라를 이용한 조사로는 어려움이 많기 때문에 하천 전체의 공간적인 하상재료 조사를 위해서는 새로운 기술이 필요하다. 이에 본 연구에서는 보다 정확한 조도계수 산정을 위해 초분광 영상을 이용하여 하상재료를 분류하고, 이를 이용하여 하천 환경 평가를 할 수 있는 하상재료 분포도를 만들기 위한 하상재료의 분광특성 분석 연구를 수행하였다. 초분광 영상의 분광특성은 수백개의 밴드가 연속적으로 구성된 정보를 말하며, 영상 내 모든 화소의 파장정보를 포함하는 데이터 큐브형식으로 구성된다. 물체의 파장정보는 분광기나 초분광 영상 촬영 장치를 통해 수집할 수 있으며 파장정보는 파장과 이에 해당하는 영역의 반사도를 측정하여 하상재료의 분광반사특성으로 확인할 수 있다. 따라서 본 연구에서는 하천의 다양한 하상재료들만의 고유 분광반사특성을 분석하여 하상재료별 분광 라이브러리를 구축하고자 한다. 또한 이와 같이 하상재료별 분광 라이브러리를 구축한 결과를 활용하여 무인기 기반의 초분광 영상을 활용한 하천 하상재료 분류 기술을 개발하고자 한다. 이를 위해 본 연구에서는 하상재료별 분광라이브러리를 구축하였고, 실제 하천에서 무인기 초분광 영상에 활용한 결과 수체가 존재하는 영역에서도 초분광 영상을 활용하여 하상재료의 분류가 가능한 것을 확인하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1176-1182
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• 2021

Recently, with the development of artificial intelligence and IoT technology, automation, and unmanned work are progressing in various fields, and the importance of image processing, which is the basis of AI object recognition, is increasing. In particular, in systems that require detailed data processing, noise removal is used as a preprocessing step, but the existing algorithm does not consider the noise level of the image, so it has the disadvantage of blurring in the filtering process. Therefore, in this paper, we propose a modified Gaussian filter that determines the weight by determining the noise level of the image. The proposed algorithm obtains the noise estimate for the AWGN of the image using quadtree segmentation, determines the Gaussian weight and the pixel weight, and obtains the final output by convolution with the local mask. To evaluate the proposed algorithm, it was simulated compared to the existing method, and superior performance was confirmed compared to the existing method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.515-523
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• 2018

In order to obtain consistent change detection result for multi-temporal satellite images, preprocessing must be performed. In particular, the preprocessing related to the spectral values can be performed by the radiometric normalization, and relative radiometric normalization is generally utilized. However, most relative radiometric normalization methods assume a linear relationship between the two images, and nonlinear spectral characteristics such as phenological differences are not considered. Therefore, this study proposes a relative radiometric normalization which assumes nonlinear relationships that can perform compositive normalization of radiometric and phenological characteristics. The proposed method selects the subject and reference images, and then extracts the radiometric control set samples through the no-change method. In addition, spectral indexes as well as pixel values are extracted in order to consider sufficient information, and modeling of nonlinear relationships is performed through multilayer perceptron. Finally, the proposed method is compared with the conventional relative radiometric normalization methods, which shows that the proposed method is visually and quantitatively superior.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1492-1499
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• 2019

This paper propose how to track the position of the observer to control the viewing zone using an adaptive parallax barrier. The pose is estimated using a Constrained Local Model based on the shape model and Landmark for robust eye-distance measurement in the face pose. Camera's correlation converts distance and horizontal location to centimeter. The pixel pitch of the adaptive parallax barrier is adjusted according to the position of the observer's eyes, and the barrier is moved to adjust the viewing area. This paper propose a method for tracking the observer in the range of 60cm to 490cm, and measure the error, measurable range, and fps according to the resolution of the camera image. As a result, the observer can be measured within the absolute error range of 3.1642cm on average, and it was able to measure about 278cm at 320×240, about 488cm at 640×480, and about 493cm at 1280×960 depending on the resolution of the image.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1520-1527
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• 2019

Superpixel methods are widely used in the preprocessing stage as a method to reduce computational complexity by simplifying images while maintaining the characteristics of images in the field of computer vision. It is common to generate superpixels with a regular size and form based on the pixel values rather than considering the characteristics of the image. In this paper, we propose a method to generate superpixels considering the characteristics of an image according to the application. The proposed method consists of two steps, and the first step is to oversegment an image so that the boundary information of the image is well preserved. In the second step, superpixels are merged based on similarity to produce the desired number of superpixels, where the form of superpixels are controlled by limiting the maximum size of superpixels. Experimental results show that the proposed method preserves the boundaries of an image more accurately than the existing method.