• Title/Summary/Keyword: Gaussian Filter(GF)

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Fingerprint Image Enhancement using a Modified Anisotropic Gaussian Filter (개선된 Anisotropic Gaussian 필터를 이용한 지문 영상 향상)

  • 조희덕;김상희;박원우
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.293-296
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    • 2003
  • The enhancement of fingerprint image is necessary to improve the performance of fingerprint recognition. The enhancement of fingerprint image with Gabor Filter(GF) is widely used. However GF has the weakness such as long processing time and the sensitivity to ridge frequency. To overcome these weaknesses, we propose a Modified Anisotropic Gaussian Filter(MAGF) which is modified from Anisotropic Filter proposed by S. Greenburg's(SAF). This proposed MAGF can reduce the calculation time of ridge frequency and improve the weakness of sensitivity to ridge frequency. We also explained that MAGF is better than others mathematically and experimentally.

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Algorithm of Adaptive Noise Reduction with Modified Sigma Filter for Reduction of Edge Blurring and Minute Noises (윤곽선 훼손 방지 및 미세잡음 제거를 위한 Modified Sigma Filter를 이용한 적응적 잡음 제거장치 알고리즘)

  • Yang, Jeong-Ju;Han, Hag-Yong;Yang, Hoon-Gee;Kang, Bong-Soon;Lee, Gi-Dong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.10
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    • pp.2261-2268
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    • 2010
  • The information captured by imaging devices such as CCD or CIS may contain external noises through the processes of passing signals or storing images. In this paper, we propose a Modified Sigma Filter (MSF) algorithm to reduce such noises. In experiment, we verified that our MSF algorithm showed better performance in PSNR and 1D plot of simulation results compared with Gaussian Filter (GF), Local Sigma Filter (LSF). Tested images include random Gaussian Noises.

High Noise Density Median Filter Method for Denoising Cancer Images Using Image Processing Techniques

  • Priyadharsini.M, Suriya;Sathiaseelan, J.G.R
    • International Journal of Computer Science & Network Security
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    • v.22 no.11
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    • pp.308-318
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    • 2022
  • Noise is a serious issue. While sending images via electronic communication, Impulse noise, which is created by unsteady voltage, is one of the most common noises in digital communication. During the acquisition process, pictures were collected. It is possible to obtain accurate diagnosis images by removing these noises without affecting the edges and tiny features. The New Average High Noise Density Median Filter. (HNDMF) was proposed in this paper, and it operates in two steps for each pixel. Filter can decide whether the test pixels is degraded by SPN. In the first stage, a detector identifies corrupted pixels, in the second stage, an algorithm replaced by noise free processed pixel, the New average suggested Filter produced for this window. The paper examines the performance of Gaussian Filter (GF), Adaptive Median Filter (AMF), and PHDNF. In this paper the comparison of known image denoising is discussed and a new decision based weighted median filter used to remove impulse noise. Using Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), and Structure Similarity Index Method (SSIM) metrics, the paper examines the performance of Gaussian Filter (GF), Adaptive Median Filter (AMF), and PHDNF. A detailed simulation process is performed to ensure the betterment of the presented model on the Mini-MIAS dataset. The obtained experimental values stated that the HNDMF model has reached to a better performance with the maximum picture quality. images affected by various amounts of pretend salt and paper noise, as well as speckle noise, are calculated and provided as experimental results. According to quality metrics, the HNDMF Method produces a superior result than the existing filter method. Accurately detect and replace salt and pepper noise pixel values with mean and median value in images. The proposed method is to improve the median filter with a significant change.

Image Restoration Algorithm Considering Pixel Distribution in AWGN Environments (AWGN 환경에서 화소 분포를 고려한 영상복원 알고리즘)

  • Kwon, Se-Ik;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.7
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    • pp.1687-1693
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    • 2015
  • Recently, demand for digital image processing devices increases rapidly, more clear images have been required. But, in the process of digital image acquisition, processing and transmission, image degradation occurs due to various external reasons and researches about noise reduction are on the rise. Therefore, this study suggested the algorithm to process AWGN(additive white Gaussian noise) by separately processing as three levels according to the pixel distribution in the mask in order to remove AWGN(additive white Gaussian noise) which is added in the image. Regarding the processed results by applying Barbara images which were damaged by AWGN(σ = 15), suggested algorithm showed the improvement by 2.87[dB], 2.95[dB], 2.88[dB], 1.52[dB], 1.49[dB], 1.58[dB] and 1.25[dB] respectively compared with the existing MF(5 × 5), A-TMF(5 × 5), AWMF(5 × 5), MF(3 × 3), A-TMF(3 × 3), AWMF(3 × 3), GF(5 × 5).