• 대한원격탐사학회지
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• 제27권6호
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• pp.693-701
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• 2011

Image registration is an essential process to analyze the time series of satellite images for the purpose of image fusion and change detection. The Mutual Information (MI) is commonly used as similarity measure for image registration because of its robustness to noise. Due to the radiometric differences, it is not easy to apply MI to multi-temporal satellite images using directly the pixel intensity. Image features for MI are more abundantly obtained by employing a Gabor filter which varies adaptively with the filter characteristics such as filter size, frequency and orientation for each pixel. In this paper we employed Bidirectional Gabor Filter Energy (BGFE) defined by Gabor filter features and applied the BGFE to similarity measure calculation as an image feature for MI. The experiment results show that the proposed method is more robust than the conventional MI method combined with intensity or gradient magnitude.

• 대한방사선기술학회지:방사선기술과학
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• 제45권5호
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• pp.397-405
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• 2022

Computed radiography (CR) systems, which convert an analog signal recorded on a cassette into a digital image, combine the characteristics of analog and digital imaging systems. Compared to digital radiography (DR) systems, CR systems have presented difficulties in evaluating system performance because of their lower detective quantum efficiency, their lower signal-to-noise ratio (SNR), and lower modulation transfer function (MTF). During the step of energy-storing and reading out, a baseline offset occurs in the edge area and makes low-frequency overestimation. The low-frequency offset component in the line spread function (LSF) critically affects the MTF and other image-analysis or qualification processes. In this study, we developed the method of baseline correction using mathematical morphology to determine the LSF and MTF of CR systems accurately. We presented a baseline correction that used a morphological filter to effectively remove the low-frequency offset from the LSF. We also tried an MTF evaluation of the CR system to demonstrate the effectiveness of the baseline correction. The MTF with a 3-pixel structuring element (SE) fluctuated since it overestimated the low-frequency component. This overestimation led the algorithm to over-compensate in the low-frequency region so that high-frequency components appeared relatively strong. The MTFs with between 11- and 15-pixel SEs showed little variation. Compared to spatial or frequency filtering that eliminated baseline effects in the edge spread function, our algorithm performed better at precisely locating the edge position and the averaged LSF was narrower.

• 한국의학물리학회지:의학물리
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• 제33권4호
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• pp.63-71
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• 2022

Purpose: To clarify the relationship between the diameter of the simulated bead and the Z-resolution of the tomosynthesis image. Methods: A simulated bead was placed on a 1,024×1,024×1,024-pixel base image. The diameters were set to 0.025, 0.05, 0.1, 0.2, 0.3, 0.7, 1.0, and 1.3 mm. A bead was placed at the center of the base image and projected at a simulated X-ray angle range of ±45° to obtain a projected image. A region of interest was placed at the center of the bead image and the slice sensitivity profile (SSP) was obtained by acquiring pixel values in the z-direction. The full width at half maximum of the SSP was defined as the Z-resolution and the frequency response was obtained by the 1-D Fourier transform of the SSP. Results: Z-resolution increased with increasing bead diameter. However, there was no change in Z-resolution between 0.025 and 0.1 mm. The frequency response was similar to that of the Z-resolution, with a significant difference between 0.1 and 0.2 mm diameter. Conclusions: Z-resolution is dependent on the diameter of the bead, which should be selected considering the pixel size of the tomosynthesis image.

• 한국정보통신학회논문지
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• 제25권10호
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• pp.1310-1316
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• 2021

최근 인공지능과 IoT 기술의 발달에 따라 물체 추적, 의료 영상, 객체 인식과 같은 영상처리에 대한 중요성이 높아지고 있다. 특히 전처리 과정에서 사용되는 잡음제거 기술은 시스템에서 영상의 중요성이 높아짐에 따라 잡음을 효율적으로 제거하며 세부적인 특징을 보존하는 성능을 요구하고 있다. 본 논문에서는 AWGN 환경에서 화소매칭 기반의 변형된 가중치 필터를 제안한다. 제안한 알고리즘은 영상에서 화소값이 크게 변하는 고주파성분을 보존하기 위해 화소매칭 기법을 사용하며, 주변 영역에서 연관성이 높은 패턴을 지닌 영역을 검출하여 출력계산에 필요한 매칭 화소값을 분류한다. 최종 출력은 필터링 과정에서 에지성분을 고려하기 위해 중심화소와 매칭화소 사이의 격차값 및 공간적 거리에 따라 가중치를 계산하여 구한다.

• ETRI Journal
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• 제45권1호
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• pp.131-137
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• 2023

The phase reconstruction process in digital holographic microscopy involves a trade-off between the phase error and the high-spatial-frequency components. In this reconstruction process, if the narrow region of the sideband is windowed in the Fourier domain, the phase error from the DC component will be reduced, but the high-spatial-frequency components will be lost. However, if the wide region is windowed, the 3D profile will include the high-spatial-frequency components, but the phase error will increase. To solve this trade-off, we propose the high-variance pixel averaging method, which uses the variance map of the reconstructed depth profiles of the windowed sidebands of different sizes in the Fourier domain to classify the phase error and the high-spatial-frequency components. Our proposed method calculates the average of the high-variance pixels because they include the noise from the DC component. In addition, for the nonaveraged pixels, the reconstructed phase data created by the spatial frequency components of the widest window are used to include the high-spatialfrequency components. We explain the mathematical algorithm of our proposed method and compare it with conventional methods to verify its advantages.

• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.457-469
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• 2003

In this paper, we have proposed the efficient algorithm that can segment the video scene change using a various statistical characteristics obtained from by applying the wavelet transformation for each frames. Our method firstly extracts the histogram features from low frequency subband of wavelet-transformed image and then uses these features to detect the abrupt scene change. Second, it extracts the edge information from applying the mesh method to the high frequency subband of transformed image. We quantify the extracted edge information as the values of variance characteristic of each pixel and use these values to detect the gradual scene change. And we have also proposed an algorithm how extract the proper key frame from segmented video scene. Experiment results show that the proposed method is both very efficient algorithm in segmenting video frames and also is to become the appropriate key frame extraction method.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
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• pp.58-61
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• 2000

In this paper, we propose a new performance comparison method of various Interpolation methods for image enlargement The conventional methods employs PSNR and edge characteristic evaluation for performance comparison of interpolation methods. The proposed performance comparison method uses the position Information for each difference pixel's value and the frequency characteristic information between original image and Interpolated image. The proposed methods might be useful for performance comparison of various Interpolation methods through the computer simulation.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 추계학술대회논문집
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• pp.503-507
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• 2004

This paper is concerned with the measurement of low-frequency vibrations of structures using the image processing method. To measure the vibrations visually, the measurement system consists of a camera, an image grabber board, and a computer. The specific target installed on the structure is used to calculate the vibration of structure. The captured image is then converted into a pixel-based data and then analyzed numerically. The limitation of the system depends on the image capturing speed and the size of image. In this paper, we discuss the methodology for the vibration measurement using the image processing method. The method enables us to measure the displacement directly without any contact. The resolution of the vibration measurement can be refined but limited to the sub centimeter displacement.

• 대한원격탐사학회지
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• 제39권6_3호
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• pp.1747-1761
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• 2023

습지는 일년 중 일정기간 물에 잠겨있거나 젖어있는 땅을 의미한다. 습지는 생물다양성 유지와 환경오염물질을 정화하는 역할을 수행하고 있다. 습지의 경계와 면적 변화에 대한 정량적인 자료를 필요로 하고 있다. 본 연구에서는 Sentinel-1 장기적인 수체 탐지 결과를 활용하여 습지의 시간에 따른 지형 변화를 매핑하고자 한다. 이를 위하여 운곡 습지와 연안 습지를 연결하는 인천강 하구 습지를 연구지역으로 설정하였다. 또한 2014년 10월 부터 2023년 3월 사이의 Sentinel-1 상향궤도 영상 196장을 수집하여 장기적인 면적 변화를 분석하였다. 픽셀-빈도기법을 적용하여 2020년을 기점으로 지형 변화를 산출하였을 때에 수위구간 2-3 m, 1-2 m, 0-1 m 그리고 0 m 이하 구간에서 각각 +0.0195, 0.0016, 0.0075 그리고 0.0163 km²의 면적 증가를 확인할 수 있었다. 이와 같은 사실에 따라 해당 지역에서의 습지 복원 사업은 유효한 것으로 판단된다.

• 한국융합학회논문지
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• 제11권12호
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• pp.15-22
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• 2020

본 논문은 채널 강조(Channel Attentin)와 공간 강조(Spatial Attention) 방법을 결합한 딥 러닝 기반의 초해상도 방법을 제안하였다. 초해상도 과정에서 질감, 특징과 같은 주변 픽셀의 변화량이 큰 고주파 성분의 복원이 중요하다. 채널 강조와 공간 강조를 결합한 특징 강조를 이용한 초해상도 방법을 제안하였다. 기존의 CNN(Convolutional Neural Network) 기반의 초해상도 방법은 깊은 네트워크의 학습이 어려우며, 고주파 성분의 강조가 부족하여 윤곽선이 흐려지거나 왜곡이 발생한다. 문제를 해결하기 위해 스킵-커넥션(Skip Connection)을 적용한 채널 강조와 공간 강조를 결합한 강조 블록과 잔차 블록(Residual Block)을 사용하였다. 방법으로 추출한 강조된 특징 맵을 부-픽셀 컨볼루션(Sub-pixel Convolution)을 통해 특징맵을 확장하여 초해상도를 진행하였다. 이를 통해 기존의 SRCNN과 비교하여 약 PSNR는 5%, SSIM은 3% 향상되었으며 VDSR과 비교를 통해 약 PSNR는 2%, SSIM은 1% 향상된 결과를 보였다.