• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.1
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• pp.75-84
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• 1998

To achieve more accurate information from satellite image data, a research on a technique for mixed pixel ex-traction has been produced. The mixed pixels with only two land covers have been experimented. By analyzing canonical vector in canonical correlation classification, the mixed pixels have been classified. The ratio of the two canonical weighted values-the elements of canonical vector have been used as a threshold to discriminate mixed pixels. In case of the classification for the mixed pixels of bridge and water class in TM data before or after the 1st of September, the threshold for the optimal classification of the mixed pixels is 4.0. That is, if the ratio of the two canonical weighted values is less than 4.0, the pixel is a mixed pixel. Also, using the distribution of canonical weighted values, the constitution percentages of land covers within one mixed pixel can be approximately deducted. The accuracy of mixed pixel extraction for experimental area is 90％ and quite acceptable. Conclusively, a technique for mixed pixel extraction by canonical vector analysis is effective.

• International Journal of Advanced Culture Technology
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• v.6 no.3
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• pp.173-177
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• 2018

Masks are generated by adding different fonts of learning data characters in pixel unit, and pixel values belonging to each of the masks are divided into 3 groups. Using the directional expansion operators, we expand the text area of the test data character into 4 diagonal directions in order to create the boundary areas to distinguish it from the background area. A mask with a minimum average discordance is selected as the final recognition result by calculating the degree of discordance between the expanded test data and the masks. Image comparison using directional expansion operations more accurately recognizes test data through 4 subdivided recognition processes. It is also possible to expand the ranges of 3 groups of pixel values of masks more evenly such that new fonts can easily be added to the given learning data.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.11a
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• pp.204-208
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• 2011

This paper proposes a novel deinterlacing algorithm using neighboring deinterlacing pixels directions weight, which can obtain the true deinterlacing direction of the interpolated pixel. The proposed algorithm determines the direction of the current interpolated pixel using MELA direction determination method. To obtain more accurate deinterlacing direction and increase interpolation direction correlation, the directions of neighboring pixels around the current interpolated pixel are considered. The current direction and the neighboring majority direction are compared to decide an interpolated method. But it cost slightly CPU time increasing since neighboring pixels directions determination and statistics. Experimental results demonstrate that the proposed algorithm outperforms the conventional deinterlacing methods.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.11a
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• pp.99-102
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• 2022

실재하는 물체나 장소를 디지털 카메라나 휴대폰 카메라로 여러 장 촬영하여 얻은 2차원 이미지 데이터셋으로부터 3차원 영상을 얻기 위해서 이미지를 이루는 각 pixel의 depth 정보를 얻는 것은 필수적인 과정이다. 주어진 이미지에서 depth 정보를 얻기 위해 Shuhan Shen은 PatchMatch 알고리즘을 활용하는 것을 제안하였다. 그 이후 PatchMatch 기반의 알고리즘은 널리 사용되며 우수한 성능을 보이고 있다. PatchMatch 기반의 알고리즘을 사용해 depth를 추정하는 과정에서 depth와 법선 벡터를 Zero-mean Normalized Cross Correlation(ZNCC)를 사용해 평가한다. 하지만, ZNCC는 depth를 평가하려는 pixel의 주변 pixel들의 밝기 값 혹은 색상 값의 분포를 사용하기 때문에 밝기 값이나 색상 값의 변화가 적은 texture-less region에서는 신뢰성이 떨어진다. 본 논문에서는 이 문제를 epipolar geometry를 활용한 기하학적 정보를 이용하여 개선하고자 한다.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.269-276
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• 2010

In this paper, we present the detection method of moving objects based on two background models. These background models support to understand multi layered environment belonged in images taken by shaking camera and each model is MBM(Multiple Background Model) and TMBM (Temporal Median Background Model). Because two background models are Pixel-based model, it must have noise by camera movement. Therefore correlation coefficient calculates the similarity between consecutive images and measures camera motion vector which indicates camera movement. For the calculation of correlation coefficient, we choose the selected region and searching area in the current and previous image respectively then we have a displacement vector by the correlation process. Every selected region must have its own displacement vector therefore the global maximum of a histogram of displacement vectors is the camera motion vector between consecutive images. The MBM classifies the intensity distribution of each pixel continuously related by camera motion vector to the multi clusters. However, MBM has weak sensitivity for temporal intensity variation thus we use TMBM to support the weakness of system. In the video-based experiment, we verify the presented algorithm needs around 49(ms) to generate two background models and detect moving objects.

• Journal of the Optical Society of Korea
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• v.16 no.4
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• pp.372-380
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• 2012

The optical method Digital Speckle Correlation Measurement (DSCM) has been extensively applied due its capability to measure the entire displacement field over a body surface. A formula of displacement measurement errors by the gradient-based DSCM method was derived. The errors were found to explicitly relate to the image grayscale errors consisting of sub-pixel interpolation algorithm errors, image noise, and subset deformation mismatch at each point of the subset. A power-law dependence of the standard deviation of displacement measurement errors on the subset size was established when the subset deformation was rigid body translation and random image noise was dominant and it was confirmed by both the numerical and experimental results. In a gradient-based algorithm the basic assumption is rigid body translation of the interrogated subsets, however, this is in contradiction to the real circumstances where strains exist. Numerical and experimental results also indicated that, subset shape function mismatch was dominant when the order of the assumed subset shape function was lower than that of the actual subset deformation field and the power-law dependence clearly broke down. The power-law relationship further leads to a simple criterion for choosing a suitable subset size, image quality, sub-pixel algorithm, and subset shape function for DSCM.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.22 no.7
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• pp.589-594
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• 2009

We have studied electro-optic characteristics as a function of passivation thickness existing between common electrode and pixel electrodes in the fringe-field switching (FFS) mode using the LC with positive dielectric anisotropy. A steep increase in the transmission is observed with increase in the passivation layer from $0.29{\mu}m$ to $1.09{\mu}m$ and thereafter it almost saturates over the $1.09{\mu}m$ of passivation layer. This saturation is mainly associated with correlation between transmittance at the center region of pixel electrode and at the center region between pixel electrodes. From the results, optimal thickness of passivation layer can be defined.

• Journal of Mechanical Science and Technology
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• v.17 no.3
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• pp.409-421
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• 2003

The hierarchical recursive local-correlation PIV algorithm with CBC (correlation based correction) method was employed to increase the spatial resolution of PIV results and to reduce error vectors. The performance of this new PIV algorithm was tested using synthetic images, PIV standard images of Visualization Society of Japan, real flows including ventilation flow inside a vehicle passenger compartment and wake behind a circular cylinder with riblet surface. As a result, most spurious vectors were suppressed by employing the CBC method, the hierarchical recursive correlation algorithm improved the sub-pixel accuracy of PIV results by decreasing the interrogation window size and Increased spatial resolution significantly. However, with recursively decreasing of interrogation window size, the SNR (signal-to-noise ratio) in the correlation plane was decreased and number of spurious vectors was increased. Therefore, compromised determination of optimal interrogation window size is required for given flow images, the performance of recursive algorithm is also discussed from a viewpoint of recovery ratio and error ratio in the paper.

• 한국가시화정보학회:학술대회논문집
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• 2001.12a
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• pp.75-85
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• 2001

The hierarchic recursive local-correlation PIV algorithm with CBC(correlation based correction) method was developed to increase the spatial resolution of PIV results and to reduce error vectors. This new algorithm was applied to the single-frame and double-frame cross-correlation PIV techniques. In order to evaluate its performance, the recursive algorithm was tested using synthetic images, PIV standard images from Visualization Society of Japan, real flows including ventilation flow inside a vehicle passenger compartment and wake behind a circular cylinder with rib let surface. As a result, most spurious vectors were suppressed by employing CBC method. In addition, the hierarchical recursive correlation algorithm improved largely the sub-pixel accuracy of PIV results by decreasing the interrogation window size, increasing spatial resolution significantly.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.706-709
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• 2002

This paper describes an effective technique for coding video sequences based on JPEG2000 codec. In the proposed method, multiple frames are combined into one large picture by interleaving each pixel data. A large picture enables images to be coded more efficiently and image quality is improved. A video sequence is efficiently coded by adapting the time correlation of the video sequences to spatial correlation. We demonstrated the effectiveness of this method by encoding video sequences using JPEG2000.