• 제목/요약/키워드: Weighted Difference Image

검색결과 98건 처리시간 0.03초

A Study on an Image Restoration Algorithm in Universal Noise Environments

  • Jin, Bo;Kim, Nam-Ho
    • Journal of information and communication convergence engineering
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    • 제6권1호
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    • pp.80-85
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    • 2008
  • Images are often corrupted by noises during signal acquisition and transmission. Among those noises, additive white Gaussian noise (AWGN) and impulse noise are most representative. For different types of noise have different characters, how to remove them separately from degraded image is one of the most fundamental problems. Thus, a modified image restoration algorithm is proposed in this paper, which can not only remove impulse noise of random values, but also remove the AWGN selectively. The noise detection step is by calculating the intensity difference and the spatial distance between pixels in a mask. To divide two different noises, the method is based on three weighted parameters. And the weighted parameters in the filtering mask depend on spatial distances, positions of impulse noise and standard deviation of AWGN. We also use the peak signal-to-noise ratio (PSNR) to evaluate restoration performance, and simulation results demonstrate that the proposed method performs better than conventional median-type filters, in preserving edge details.

Analysis of Image Distortion on Magnetic Resonance Diffusion Weighted Imaging

  • Cho, Ah Rang;Lee, Hae Kag;Yoo, Heung Joon;Park, Cheol-Soo
    • Journal of Magnetics
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    • 제20권4호
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    • pp.381-386
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    • 2015
  • The purpose of this study is to improve diagnostic efficiency of clinical study by setting up guidelines for more precise examination with a comparative analysis of signal intensity and image distortion depending on the location of X axial of object when performing magnetic resonance diffusion weighted imaging (MR DWI) examination. We arranged the self-produced phantom with a 45 mm of interval from the core of 44 regent bottles that have a 16 mm of external diameter and 55 mm of height, and were placed in 4 rows and 11 columns in an acrylic box. We also filled up water and margarine to portrait the fat. We used 3T Skyra and 18 Channel Body array coil. We also obtained the coronal image with the direction of RL (right to left) by using scan slice thinkness 3 mm, slice gap: 0mm, field of view (FOV): $450{\times}450mm^2$, repetition time (TR): 5000 ms, echo time (TE): 73/118 ms, Matrix: $126{\times}126$, slice number: 15, scan time: 9 min 45sec, number of excitations (NEX): 3, phase encoding as a diffusion-weighted imaging parameter. In order to scan, we set b-value to $0s/mm^2$, $400s/mm^2$, and $1,400s/mm^2$, and obtained T2 fat saturation image. Then we did a comparative analysis on the differences between image distortion and signal intensity depending on the location of X axial based on iso-center of patient's table. We used "Image J" as a comparative analysis programme, and used SPSS v18.0 as a statistic programme. There was not much difference between image distortion and signal intensity on fat and water from T2 fat saturation image. But, the average value depends on the location of X axial was statistically significant (p < 0.05). From DWI image, when b-value was 0 and 400, there was no significant difference up to $2^{nd}$ columns right to left from the core of patient's table, however, there was a decline in signal intensity and image distortion from the $3^{rd}$ columns and they started to decrease rapidly at the $4^{th}$ columns. When b-value was 1,400, there was not much difference between the $1^{st}$ row right to left from the core of patient's table, however, image distortion started to appear from the $2^{nd}$ columns with no change in signal intensity, the signal was getting decreased from the $3^{rd}$ columns, and both signal intensity and image distortion started to get decreased rapidly. At this moment, the reagent bottles from outside out of 11 reagent bottles were not verified from the image, and only 9 reagent bottles were verified. However, it was not possible to verify anything from the $5^{th}$ columns. But, the average value depends on the location of X axial was statistically significant. On T2 FS image, there was a significant decline in image distortion and signal intensity over 180mm from the core of patient's table. On diffusion-weighted image, there was a significant decline in image distortion and signal intensity over 90 mm, and they became unverifiable over 180 mm. Therefore, we should make an image that has a diagnostic value from examinations that are hard to locate patient's position.

뇌경색 시기별 MR영상의 정량적 분석 (Quantitative Analysis of MR Image in Cerebral Infarction Period)

  • 박병래;하광;김학진;이석홍;전계록
    • 대한방사선기술학회지:방사선기술과학
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    • 제23권1호
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    • pp.39-47
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    • 2000
  • In this study, we showed a comparison and analysis making use of DWI(diffusion weighted image) using early diagnosis of cerebral Infarction and with the classified T2 weighted image, FLAIR images signal intensity for brain infarction period. period of cerebral infarction after the condition of a disease by ischemic stroke. To compare 3 types of image, we performed polynomial warping and affined transform for image matching. Using proposed algorithm, calculated signal intensity difference between T2WI, DWI, FLAIR and DWI. The quantification values between hand made and calculated data are almost the same. We quantified the each period and performed pseudo color mapping by comparing signal intensity each other according to previously obtained hand made data, and compared the result of this paper according to obtained quantified data to that of doctors decision. The examined mean and standard deviation for each brain infarction stage are as follows ; the means and standard deviations of signal intensity difference between DWI and T2WI for each period are $197.7{\pm}6.9$ in hyperacute, $110.2{\pm}5.4$ in acute, and $67.8{\pm}7.2$ in subacute. And the means and standard deviations of signal intensity difference between DWI and FLAIR for each period are $199.8{\pm}7.5$ in hyperacute, $115.3{\pm}8.0$ in acute, and $70.9{\pm}5.8$ in subacute. We can quantificate and decide cerebral infarction period objectively. According to this study, DWI is very exact for early diagnosis. We classified the period of infarction occurrence to analyze the region of disease and normal region in DW, T2WI, FLAIR images.

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Planar Region Extraction for Visual Navigation using Stereo Cameras

  • Lee, Se-Na;You, Bum-Jae;Ko, Sung-Jea
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.681-686
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    • 2003
  • In this paper, we propose an algorithm to extract valid planar regions from stereo images for visual navigation of mobile robots. The algorithm is based on the difference image between the stereo images obtained by applying Homography matrix between stereo cameras. Illegal planar regions are filtered out by the use of labeling of the difference images and filtering of invalid blobs using the size of each blob. Also, illegal large planar regions such as walls are removed by adopting a weighted low-pass filtering of the difference image using the past difference images. The algorithms are experimented successfully by the use of stereo camera system built in a mobile robot and a PC-based real-time vision system.

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WENO 방법을 이용한 UHD TV 화질 개선 (WENO methodology for UHD TV Image Quality Improvement)

  • 이덕균;박지은
    • 디지털융복합연구
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    • 제16권4호
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    • pp.149-155
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    • 2018
  • FHD(Full High Definition Television)의 시대를 지나 UHD(Ultra High Definition Television) 시대를 맞이하였다. 두 TV에서 화소(Pixel)수의 차이에 따라 발생하는 문제에 대하여 이야기하고 이를 개선할 수 있는 방법을 도입하고자 한다. 이 방법은 WENO(Weighted Essential Non-Oscillation)으로 주어진 영상(Image)에 적합한 보간법을 시행하는 방법이다. 이를 통하여 영상의 왜곡현상을 줄이고 보다 나은 화질을 보장할 수 있다. 따라서 예전에 만들어진 영상물을 UHD TV로 시청하려고 할 때 WENO 방법론을 활용하면 화소수에 따른 화질의 저하 없이 UHD TV의 고화질을 누릴 수 있다.

Restoration of Images Contaminated by Mixed Gaussian and Impulse Noise using a Complex Method

  • Yinyu, Gao;Kim, Nam-Ho
    • Journal of information and communication convergence engineering
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    • 제9권3호
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    • pp.336-340
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    • 2011
  • Many approaches to image restoration are aimed at removing either gauss or impulse noise. This is because both types of degradation processes are distinct in nature, and hence they are easier to manage when considered separately. Nevertheless, it is possible to find them operating on the same image, which produces a hard damage. This happens when an image, already contaminated by Gaussian noise in the image acquisition procedure, undergoes impulsive corruption during its digital transmission. Here we proposed an algorithm first judge the type of the noise according to the difference values of pixel's neighborhood region and impulse noise's characteristic. Then removes the gauss noise by modified weighted mean filter and removes the impulse noise by modified nonlinear filter. The result of computer simulation on test images indicates that the proposed method is superior to traditional filtering algorithms. The proposed method can not only remove mixed noise effectively, but also preserve image details.

가중치 차 영상과 움직임 벡터를 이용한 두드러진 움직임 정보 검출 방법 (Salient Motion Information Detection Method Using Weighted Subtraction Image and Motion Vector)

  • 김선우;하태령;박춘배;최연성
    • 한국정보통신학회논문지
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    • 제11권4호
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    • pp.779-785
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    • 2007
  • 비디오 감시를 위한 움직이는 객체의 검출은 매우 중요하다. 많은 환경에서 움직임은 관심 있는 움직임과 관심없는 움직임으로 나눌 수 있다. 관심 있는 움직임을 갖는 연구는 이미 많은 논의가 있어 왔다. 이 논문에서, 우리는 최신의 MPEG-4 EPZS 알고리즘을 이용한 움직임 벡터로부터 많은 움직임을 갖는 블록 영상을 구한 뒤, 시간에 대한 가중치를 부여한 차 영상과의 결합에 의한 복합적인 환경에서의 현저한 움직임 검출 방법을 제안한다. 우리의 방법은 기존의 배경 차 방법과 비교하여 눈에 띄게 좋은 결과영상을 얻을 수 있었다. 제안된 검출 방법은 다른 움직임의 간섭이 있는 복잡한 환경에서의 객체검출에 매우 효과적이다.

이미지 검색을 위한 칼라 분포 기술자의 성능 평가 (An Empirical Evaluation of Color Distribution Descriptor for Image Search)

  • 이춘상;이요환;김영섭;이상범
    • 반도체디스플레이기술학회지
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    • 제5권2호
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    • pp.27-31
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    • 2006
  • As more and more digital images are made by various applications, image retrieval becomes a primary concern in technology of multimedia. This paper presents color based descriptor that uses information of color distribution in color images which is the most basic element for image search and performance of proposed visual feature is evaluated through the simulation. In designing the image search descriptor used color histogram, HSV, Daubechies 9/7 and 2 level wavelet decomposition provide better results than other parameters in terms of computational time and performances. Also histogram quadratic matrix outperforms the sum of absolute difference in similarity measurements, but spends more than 60 computational times.

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확산강조영상 검사 시 rectangular FOV 적용에 따른 ADC 값의 변화 (A Change of Apparent Diffusion Coefficient in Diffusion Weighted Imaging Applied with Rectangular FOV Technique)

  • 나사라;최관우;구노현;유병규;손순룡
    • 한국방사선학회논문지
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    • 제10권7호
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    • pp.545-550
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    • 2016
  • 본 연구는 MRI를 이용한 기능검사 시 rectangular FOV를 적용하더라도 기능을 정량화한 대표 값은 차이가 없다는 것을 증명함으로써, FOV 불일치로 인해 발생되는 문제점을 개선하고자 하였다. 연구방법은 대표적인 기능 검사로 뇌졸증의 진단에 널리 사용되고 있는 확산강조영상 검사를 이용하여, 주파수부호화 방향의 FOV 변화에 따른 ADC 값의 변화 여부를 비교평가 하였다. 연구결과, 주파수부호화 방향의 FOV가 변화함에 따라 ADC값은 통계적으로 유의한 차이를 보이지 않았으며, 사후분석 결과도 유의수준 0.05에 대한 부집단이 모두 1개 밖에 존재하지 않아 FOV 변화에 따른 ADC 값의 차이가 없음을 알 수 있었다. 결론적으로 MRI를 이용한 기능 영상에서 rectangular FOV를 적용하더라도 기능을 정량화한 대표 값에는 차이가 없으므로, FOV 불일치로 인해 수반되는 공간왜곡이나 mismatching의 문제점을 개선할 수 있다.

Modified Cubic Convolution Interpolation for Low Computational Complexity

  • Jun, Young-Hyun;Yun, Jong-Ho;Choi, Myung-Ryul
    • 한국정보디스플레이학회:학술대회논문집
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    • 한국정보디스플레이학회 2006년도 6th International Meeting on Information Display
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    • pp.1259-1262
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    • 2006
  • In this paper, we propose a modified cubic convolution interpolation for the enlargement or reduction of digital images using a pixel difference value. The proposed method has a low complexity: the number of multiplier of weighted value to calculate one pixel of a scaled image has seven less than that of cubic convolution interpolation has sixteen. We use the linear function of the cubic convolution and the difference pixel value for selecting interpolation methods. The proposed method is compared with the conventional one for the computational complexity and the image quality. The simulation results show that the proposed method has less computational complexity than one of the cubic convolution interpolation.

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