• Title/Summary/Keyword: Pixel gradient

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Similarity Measurement using Gabor Energy Feature and Mutual Information for Image Registration

  • Ye, Chul-Soo
    • Korean Journal of Remote Sensing
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    • v.27 no.6
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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.

Morphological Operations to Segment a Tumor from a Magnetic Resonance Image

  • Thapaliya, Kiran;Kwon, Goo-Rak
    • Journal of information and communication convergence engineering
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    • v.12 no.1
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    • pp.60-65
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    • 2014
  • This paper describes an efficient framework for the extraction of a brain tumor from magnetic resonance (MR) images. Before the segmentation process, a median filter is used to filter the image. Then, the morphological gradient is computed and added to the filtered image for intensity enhancement. After the enhancement process, the thresholding value is calculated using the mean and the standard deviation of the image. This thresholding value is used to binarize the image followed by the morphological operations. Moreover, the combination of these morphological operations allows to compute the local thresholding image supported by a flood-fill algorithm and a pixel replacement process to extract the tumor from the brain. Thus, this framework provides a new source of evidence in the field of segmentation that the specialist can aggregate with the segmentation results in order to soften his/her own decision.

Local stereo matching using combined matching cost and adaptive cost aggregation

  • Zhu, Shiping;Li, Zheng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.1
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    • pp.224-241
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    • 2015
  • Multiview plus depth (MVD) videos are widely used in free-viewpoint TV systems. The best-known technique to determine depth information is based on stereo vision. In this paper, we propose a novel local stereo matching algorithm which is radiometric invariant. The key idea is to use a combined matching cost of intensity and gradient based similarity measure. In addition, we realize an adaptive cost aggregation scheme by constructing an adaptive support window for each pixel, which can solve the boundary and low texture problems. In the disparity refinement process, we propose a four-step post-processing technique to handle outliers and occlusions. Moreover, we conduct stereo reconstruction tests to verify the performance of the algorithm more intuitively. Experimental results show that the proposed method is effective and robust against local radiometric distortion. It has an average error of 5.93% on the Middlebury benchmark and is compatible to the state-of-art local methods.

A study on the effect of JPEG recompression with the color image quality (JPEG 재압축이 컬러 이미지 품질에 미치는 영향에 관한 연구)

  • 이성형;조가람;구철희
    • Journal of the Korean Graphic Arts Communication Society
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    • v.18 no.2
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    • pp.55-68
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    • 2000
  • Joint photographic experts group (JPEG) is a standard still-image compression technique, established by the international organization for standardization (ISO) and international telecommunication standardization sector (ITUT). The standard is intended to be utilized in the various kinds of color still imaging systems as a standard color image coding format. Because JPEG is a lossy compression, the decompressed image pixel values are not the same as the value before compression. Various distortions of JPEG compression and JPEG recompression has been reported in various papers. The Image compressed by JPEG is often recompressed by same type compression method in JPEG. In general, JPEG is a lossy compression and the quality of compressed image is predicted that is varied in according to recompression Q-factor. In this paper, four difference color samples(photo image, gradient image, gradient image, vector drawing image, text image) were compressed in according to various Q-factor, and then the compressed images were recompressed according to various Q-factor once again. As the result, this paper evaluate the variation of image quality and file size in JPEG recompression and recommed the optimum recompression factor.

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Visualization Method for Boundary Region Using Transfer Function in 3D Data Set (3D Data Set에서 Transfer Function를 이용한 경계 영역의 가시화 방법)

  • 박재영;이병일;최현주;최흥국
    • Proceedings of the Korea Multimedia Society Conference
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    • 2000.04a
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    • pp.425-428
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    • 2000
  • 2차원 슬라이스 영상으로부터 volume rendered 이미지를 생성하기 위해서는 2차원 영상의 pixel 데이터를 voxel 기반으로 재구성해야 한다. 영상을 재구성하면서 생성되는 voxel value 는 3차원 영상을 2차원 화면으로 원근 투영할 때 최종 픽셀값을 결정하는 기본 요소가 된다. 따라서 본 논문에서는 조합되는 voxel value를 결정하는 Transfer Function를 이용한 intensity 와 gradient magnitude 의조작을 통하여 최종 3차원 이미지에서 오브젝트의 surface 뿐만 아니라 내부의 서로 다른 조직끼리의 경계 영역을 가시화하여 보았다.

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Image Segmentation Using Level Set Method with New Speed Function (새로운 속도함수를 갖는 레벨 셋 방법을 이용한 의료영상분할)

  • Kim, Sun-Worl;Cho, Wan-Hyun
    • The Korean Journal of Applied Statistics
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    • v.24 no.2
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    • pp.335-345
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    • 2011
  • In this paper, we propose a new hybrid speed function for image segmentation using level set. A new proposed speed function uses the region and boundary information of image object for the exact result of segmentation. The region information is defined by the probability information of pixel intensity in a ROI(region-of-interest), and the boundary information is defined by the gradient vector flow obtained from the gradient of image. We show the results of experiment for an various artificial image and real medical image to verify the accuracy of segmentation using proposed method.

Edge Detection Using the Information of Edge Structural Regions (에지의 구조적 영역정보를 이용한 에지검출)

  • 김수겸;박중순;최정희
    • Journal of Advanced Marine Engineering and Technology
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    • v.24 no.2
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    • pp.82-89
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    • 2000
  • Edge detection is the first step and very important step in image analysis. In this paper, proposed edge detection operators based on informations of edge types and it is different from other classical edge detection operators such as gradient and surface fitting operators. The first, we defined characteristics of edge types such as localization, thinness, length. The second, we defined valid edge types and ideal edge pixel positions in $3\times3$window based on edge characteristics of edge types. And we proposed edge detection algorithm and twelve windows based on valid edge types. In specially, proposed algorithm was shown better performence of edge detection than other operators such as gradient operator and the LoG(Laplacian of Gaussian) operator of zero crossings.

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Feature extraction motivated by human information processing method and application to handwritter character recognition (인간의 정보처리 방법에 기반한 특징추출 및 필기체 문자인식에의 응용)

  • 윤성수;변혜란;이일병
    • Korean Journal of Cognitive Science
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    • v.9 no.1
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    • pp.1-11
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    • 1998
  • In this paper, the features which are thought to be used by humans based on the psychological experiment of human information processing are applied to character recognition problem. Man will deal with a little large area information as well as pixel by pixel information. Therefore we define the feature that represents a little wide region I information called region feature, and combine the features derived from region feature and pixel by pixel features that have been used by now. The features we used are the result of region feature based preanalysis, mesh with region attributes, cross distance difference and gradient. The training and test data in the experiment are handwritten Korean alphabets, digits and English alphabets, which are trained on neural network using back propagation algorithm and recognition results are 90.27-93.25%, 98.00% and 79.73-85.75%, respectively Experimental results show that the feature we are suggesting in this paper is 1-2% better than UDLRH feature similar in attribute to region feature, and the tendency of misrecognition is more easily acceptable by humans.

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Adaptive Weight Adjusted Catmull-Rom Spline Interpolation Based on Pixel Intensity Variation for Medical Imaging Volume Visualization (의료영상 볼륨가시화를 위한 화소 값의 변화도에 따른 적응적 가중치를 적용한 캐트멀-롬 스플라인 보간법)

  • Lee, Hae-Na;Yoo, Sun K.
    • Journal of Korea Multimedia Society
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    • v.16 no.2
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    • pp.147-159
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    • 2013
  • In medical visualization, volume visualization is widely used. Applying 3D images to diagnose requires high resolution and accurately implement visualization techniques are being researched accordingly. However, when a three-dimensional image volume visualization is implemented using volume data, aliasing will occur since using discrete data. Supersampling method, getting lots of samples, is used to reduce artifacts. One of the supersampling methods is Catmull-rom spline. This method calculates accurate interpolation value because it is easy to compute and pass through control points. But, Catmull-rom spline method occurs overshoot or undershoot in large gradient of pixel values. So, interpolated values are different from original signal. In this paper, we propose an adaptive adjusting weights interpolation method using Gaussian function. Proposed method shows that overshoot is reduced on the point has a large gradient and PSNR is higher than other interpolated image results.

Edge Detection Using Informations of Edge Structures (에지의 구조적정보을 이용한 에지추출)

  • Kim, Su-Gyeom;Jang, Yu-Jeong
    • The Transactions of the Korea Information Processing Society
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    • v.3 no.5
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    • pp.1337-1345
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    • 1996
  • Edge detection is the first step and very important step in image nalyisi. In this paper, proposed edge detection algorithm based on informations of edge structures and it is different from other classical edge detection operators such asgradient and surface fitting algorithm. The firs, we defined characteristics of edge structures such as continuity, thinness, localization, length. The second, we defined valid edge structures and ideal edge pixel positions in $3\times3$ window based on edge characteristics of edge structures. And we proposed twelve windows for enhance dissimilarity regions based on valid edge structures and ideal edge pixel positions. In specially, proposed algorithm was shown better performance of edge detection than other operators such as gradient operator and the LoG(Laplacian of gradient) operator of zero crossings in noisy test image with $\sigma=30$.

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