• Title/Summary/Keyword: Gaussian high-pass filter

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Image Processing Using Multiplierless Binomial QMF-Wavelet Filters (곱셈기가 없는 이진수 QMF-웨이브렛 필터를 사용한 영상처리)

  • 신종홍;지인호
    • Journal of Broadcast Engineering
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    • v.4 no.2
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    • pp.144-154
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    • 1999
  • The binomial sequences are family of orthogonal sequences that can be generated with remarkable simplicity-no multiplications are necessary. This paper introduces a class of non-recursive multidimensional filters for frequency-selective image processing without multiplication operations. The magnitude responses are narrow-band. approximately gaussian-shaped with center frequencies which can be positioned to yield low-pass. band-pass. or high-pass filtering. Algorithms for the efficient implementation of these filters in software or in hardware are described. Also. we show that the binomial QMFs are the maximally flat magnitude square Perfect Reconstruction paraunitary filters with good compression capability and these are shown to be wavelet filters as well. In wavelet transform the original image is decomposed at different scales using a pyramidal algorithm architecture. The decomposition is along the vertical and horizontal direction and maintains constant the number of pixels required to describe the images. An efficient perfect reconstruction binomial QMF-Wavelet signal decomposition structure is proposed. The technique provides a set of filter solutions with very good amplitude responses and band split. The proposed binomial QMF-filter structure is efficient, simple to implement on VLSl. and suitable for multi-resolution signal decomposition and coding applications.

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An Algorithm of Welding Bead Detection and Evaluation Using and Multiple Filters Geodesic Active Contour (다중필터와 축지적 활성 윤곽선 알고리즘을 이용한 용접 비드 검출 및 판단 알고리즘)

  • Milyahilu, John;Kim, Young-Bong;Lee, Jae Eun;Kim, Jong-Nam
    • Journal of the Institute of Convergence Signal Processing
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    • v.22 no.3
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    • pp.141-148
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    • 2021
  • In this paper, we propose an algorithm of welding bead detection and evaluation using geodesic active contour algorithm and high pass filter with image processing technique. The algorithm uses histogram equalization and high pass filter as gaussian filter to improve contrast. The image processing techniques smoothens the welding beads reduce the noise on an image. Then, the algorithm detects the welding bead area by applying the geodesic active contour algorithm and morphological ooperation. It also applies the balloon force that either inflates in, or deflates out the evolving contour for a better segmentation. After that, we propose a method for determining the quality of welding bead using effective length and width of the detected bead. In the experiments, our algorithm achieved the highest recall, precision, F-measure and IOU as 0.9894, 0.9668, 0.9780, and 0.8957 respectively. We compared the proposed algorithm with the conventional algorithms to evaluate the performance of the proposed algorithm. The proposed algorithm achieved better performance compared to the conventional ones with a maximum computational time of 0.6 seconds for segmenting and evaluating one welding bead.

Automatic Identification of Fiducial Marks Based on Weak Constraints

  • Cho, Seong-Ik;Kim, Kyoung-Ok
    • Korean Journal of Remote Sensing
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    • v.19 no.1
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    • pp.61-70
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    • 2003
  • This paper proposes an autonomous approach to localize the center of fiducial marks included in aerial photographs without precise geometric information and human interactions. For this localization, we present a conceptual model based on two assumptions representing symmetric characteristics of fiducial area and fiducial mark. The model makes it possible to locate exact center of a fiducial mark by checking the symmetric characteristics of pixel value distribution around the mark. The proposed approach is composed of three steps: (a) determining the symmetric center of fiducial area, (b) finding the center of a fiducial mark with unit pixel accuracy, and finally (c) localizing the exact center up to sub-pixel accuracy. The symmetric center of the mark is calculated tv successively applying three geometric filters: simplified ${\nabla}^2$G (Laplacian of Gaussian) filter, symmetry enhancement filter, and high pass filter. By introducing a self-diagnosis function based on the self-similarity measurement, a way of rejecting unreliable cases of center calculation is proposed, as well. The experiments were done with respect to 284 samples of fiducial marks composed of RMK- and RC-style ones extracted from 51 scanned aerial photographs. It was evaluated in the visual inspection that the proposed approach had resulted the erroneous identification with respect to only one mark. Although the proposed approach is based on weak constraints, being free from the exact geometric model of the fiducial marks, experimental results showed that the proposed approach is sufficiently robust and reliable.

Variation of the Sea Level in the Korean seas Using Altimeter Data (TOPEX/POSEIDON)

  • Seo, Won-Chan;Yoon, Hong-Joo
    • Journal of information and communication convergence engineering
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    • v.6 no.4
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    • pp.430-433
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    • 2008
  • A merged altimeter data products are used to estimate sea level variation in the East Sea between 1993 and 2006. The altimeter data show a high correlation coefficient (0.85) after applying gaussian low pass filter for 180days at Ulleung island. The both of Mukho coast and Ulleung island are minimal sea level in March to May and maximal in September to November. Sea level of Mukho coast is higher than that of Ulleung island during March to May, while Mukho coast is lower during September to November because the North Korea Cold Current flows along the coast line of Mukho. Generally sea level variation at Mukho coast and Ulleung island associated with seasonal variations.

AWGN Removal using Pixel Noise Characteristics of Image (영상의 잡음 특성 추정을 이용한 AWGN 제거)

  • Cheon, Bong-Won;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.12
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    • pp.1551-1557
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    • 2019
  • In modern society, a variety of video media have been widely spread in line with the fourth industrial revolution and the development of IoT technology; in accordance with this trend, numerous researches have been performed to remove noise generated in image and data communications. However, the conventional Additive White Gaussian Noise (AWGN) cancellation techniques are likely to induce a blurring phenomenon in the noise removal process, thus impairing the information of the image. In this study, we propose an algorithm for minimizing the loss of image information in the removal process of AWGN. The proposed algorithm can apply weights according to the characteristics of noise by predicting AWGN in the image, where the output is calculated based on adding and subtracting the outputs of the high pass filter and the low pass filter. Compared to the existing method, the noise reduction using the proposed algorithm exhibited less blurring issues and better noise reduction properties in the AWGN removal process.

Sharpness Measure Based on the Frequency Domain Information (주파수 도메인 정보를 이용한 영상의 Sharpness 평가 방법)

  • Choi, Hyun-Soo;Lee, Chul-Hee
    • Journal of Broadcast Engineering
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    • v.16 no.3
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    • pp.552-560
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    • 2011
  • In this paper, a new no-reference sharpness measure using frequency domain coefficients is proposed. Although most existing sharpness measures used pixel intensity to compute the blur degree, the proposed sharpness measure computes the sharpness using frequency coefficients. To assess the perceived sharpness of a given image, the image is re-blurred by a Gaussian low pass filter and a new quality measure function was defined using the frequency domain coefficients of the given image and the re-blurred image. To evaluate the proposed algorithms, TID2008 quality assessment database was used. Experimental results show that the proposed quality assessment method showed high correlation with the subjective scores.