• Title/Summary/Keyword: Laplacian of the Gaussian

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FUSESHARP: A MULTI-IMAGE FOCUS FUSION METHOD USING DISCRETE WAVELET TRANSFORM AND UNSHARP MASKING

  • GARGI TRIVEDI;RAJESH SANGHAVI
    • Journal of applied mathematics & informatics
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    • v.41 no.5
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    • pp.1115-1128
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    • 2023
  • In this paper, a novel hybrid method for multi-focus image fusion is proposed. The method combines the advantages of wavelet transform-based methods and focus-measure-based methods to achieve an improved fusion result. The input images are first decomposed into different frequency sub-bands using the discrete wavelet transform (DWT). The focus measure of each sub-band is then calculated using the Laplacian of Gaussian (LoG) operator, and the sub-band with the highest focus measure is selected as the focused sub-band. The focused sub-band is sharpened using an unsharp masking filter to preserve the details in the focused part of the image.Finally, the sharpened focused sub-bands from all input images are fused using the maximum intensity fusion method to preserve the important information from all focus images. The proposed method has been evaluated using standard multi focus image fusion datasets and has shown promising results compared to existing methods.

Performance Comparisons of some nonparametric detectors (몇가지 비모수 검파기의 성능 비교)

  • 김홍길;송익호;장태주;배진수
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 1996.06a
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    • pp.9-15
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    • 1996
  • In this paper, we propose a new detector based on the median-shift sign. We call it the median-shift sign (MSS) detector, which is an extension of the classical sign detector. We first analyze the problem of detecting a dc signal in noise of known probability density function (pdf). The MSS detector with the optimum median-shift value, the optimum MSS detector, performs better than the sign detector in Gaussian noise: it has the best performance among the detectors compared in Laplacian and Cauchy noise. It is shown that the MSS detectors with constant median-shift values are nearly equal to the optimum MSS detector. We also analyze the problem of detecting a dc signal when only partial information is available on the noise. The MSS detectors with constant median-shift values are almost equal to the sign detector in Gaussian noise: they perform better than the sign and Wilcoxon detectors for most signal ranges in Laplacian and Cauchy noise.

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Distribution Approximation of the Two Dimensional Discrete Cosine Transform Coefficients of Image (영상신호 2차원 코사인 변환계수의 분포근사화)

  • 심영석
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.10 no.3
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    • pp.130-134
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    • 1985
  • In two-dimensional discrete cosine transform(DCT) coding, the measurements of the distributions of the transform coefficients are important because a better approximation yields a smaller mean square distorition. This paper presents the results of distribution tests which indicate that the statistics of the AC coefficients are well approximated to a generalized Gaussian distribution whose shape parameter is 0.6. Furthermore, from a simulation of the DCT coding, it was shown that the above approximation yields a higher experimental SNR and a better agreement between theory and simulation than the Gaussian or Laplacian assumptions.

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Development of Real-time Landslide Inspecting and Monitoring System

  • Hur Chul;Jeon, Yang-Bae;Kim, Choon-Sik;Kim, Sang-Bong
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.243-243
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    • 2000
  • This paper introduces a visual inspecting and monitoring system based on an image processing technique. We propose an image processing method for analyzing landslide movement in real time. The method adopts Laplacian of Gaussian operator to extract linear features for the captured images and uses a linear matching algorithm to distinguish the matching error for those features. When the algorithm is processed, motion parameters such as displacement area and its direction are computed. Once movement is recognized, displacements are estimated graphically with statistical amount in the image plane. The simulation results are shown us to verify the effectiveness of the developed method.

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An Edge Detection Algorithm using Modified Mask in AWGN Environment (AWGN 환경에서 변형된 마스크를 이용한 에지 검출 알고리즘)

  • Lee, Chang-Young;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.05a
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    • pp.892-894
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    • 2013
  • Edge has been utilized in various application fields with development of technique of digital image processing. In conventional edge detection methods, there are some methods using mask including Sobel, Prewitt, Roberts and Laplacian operator. Those methods are that implement is simple but generates errors of edge detection in images added AWGN(additive white Gaussian noise). Therefore, to compensate the defect of those methods, in this paper, an edge detection algorithm using modified mask is proposed, and it showed superior edge detection property in AWGN.

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Analysis on the Regularization Parameter in Image Restoration (영상복원에서의 정칙화 연산자 분석)

  • 전우상;이태홍
    • Journal of Korea Multimedia Society
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    • v.2 no.3
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    • pp.320-328
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    • 1999
  • The Laplacian operator is usually used as a regularization operator which may be used as any differential operator in the regularization iterative restoration. In this paper, several kinds of differential operator and 1-H operator that has been used in our lab as well, as a regularization operator, were compared with each other. In the restoration of noisy motion-blurred images, 1-H operator worked better than Laplacian operator in flat region, but in the edge the Laplacian operator operated better. For noisy gaussian-blurred image, 1-H operator worked better in the edge, while in flat region the Laplacian operator resulted better. In regularization, smoothing the noise and resorting the edges should be considered at the same time, so the regions divided into the flat, the middle, and the detailed, which were processed in separate and compared their MSE. Laplacian and 1-H operator showed to be suitable as the regularization operator, while the other differential operators appeared to be diverged as iterations proceeded.

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Feature extraction method using graph Laplacian for LCD panel defect classification (LCD 패널 상의 불량 검출을 위한 스펙트럴 그래프 이론에 기반한 특성 추출 방법)

  • Kim, Gyu-Dong;Yoo, Suk-I.
    • Proceedings of the Korean Information Science Society Conference
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    • 2012.06b
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    • pp.522-524
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    • 2012
  • For exact classification of the defect, good feature selection and classifier is necessary. In this paper, various features such as brightness features, shape features and statistical features are stated and Bayes classifier using Gaussian mixture model is used as classifier. Also feature extraction method based on spectral graph theory is presented. Experimental result shows that feature extraction method using graph Laplacian result in better performance than the result using PCA.

Adaptive Feedback Cancellation Using by Independent Component Analysis for Digital Hearing Aid (독립성분분석을 이용한 디지털 보청기용 적응형 궤환 제거)

  • Ji, Yoon-Sang;Lee, Sang-Min;Jung, Sae-Young;Kim, In-Young;Kim, Sun-I
    • Speech Sciences
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    • v.12 no.3
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    • pp.79-89
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    • 2005
  • Acoustic feedback between microphone and receiver can be effectively cancelled adaptive feedback cancellation algorithm. Although many speech sounds have non-Gaussian distribution, most algorithms were tested with speech like sounds whose distribution were Guassian type. In this paper, we proposed an adaptive feedback cancellation algorithm based on independent component analysis (ICA) for digital hearing aid. The algorithm was tested with not only Gaussian distribution but also Laplacian distribution. We verified that the proposed algorithm has better acoustic feedback cancelling performance than conventional normalized root mean square (NLMS) algorithm, especially speech like sounds with Laplacian distribution.

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Study of High Speed Image Registration using BLOG (BLOG를 이용한 고속 이미지 정합에 관한 연구)

  • Kim, Jong-Min;Kang, Myung-A
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.11
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    • pp.2478-2484
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    • 2010
  • In this paper, real-time detection methods for Panorama system Key-Points offers. A recent study in PANORAMA system real-time area navigation or DVR to apply such research has recently been actively. The detection of the Key-Point is the most important elements that make up a Panorama system. Not affected by contrast, scale, Orientation must be detected Key-Point. Existing research methods are difficult to use in real-time Because it takes a lot of computation time. Therefore, this paper propose BLOG(BitRate Laplacian Of Gaussian)method for faster time Key-Point Detecting and Through various experiments to detect the Speed, Computation, detection performance is compared against.

Comparative Analysis of Detection Algorithms for Corner and Blob Features in Image Processing

  • Xiong, Xing;Choi, Byung-Jae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.13 no.4
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    • pp.284-290
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    • 2013
  • Feature detection is very important to image processing area. In this paper we compare and analyze some characteristics of image processing algorithms for corner and blob feature detection. We also analyze the simulation results through image matching process. We show that how these algorithms work and how fast they execute. The simulation results are shown for helping us to select an algorithm or several algorithms extracting corner and blob feature.