• Title/Summary/Keyword: Daubechies Filtering

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Embedded Zerotree Wavelet Image Compression using Daubechies Filtering (Daubechies Filtering을 이용한 EZW 영상 압축)

  • Kim, Jang-Won;Song, Dae-Geon
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.2 no.4
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    • pp.19-28
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    • 2009
  • This paper is a study on method that the EZW algorithm is proposed effective compression technique of wavelet transformed image. The EZW algorithm is encoded by zerotree coding technique using self-similarity of wavelet coefficients. If the coefficient is larger than the threshold a POS coded, if the coefficients is smaller than minus the threshold a NEG is coded. If the coefficient is the root of a zerotree than a ZTR is coded and finally, if the coefficient is smaller then the threshold but it is not the root of a zerotree, than an IZ is coded. This process is repeated until all the wavelet coefficients have been encoded completely. This paper was compared to EZW algorithm and a widely available version of JPEG. As the results of compare, it is shown that the PSNR of the EZW algorithm is better than JPEG.

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Filtering in composite materials C-scan image (복합재료의 C-scan영상에서의 오류 검출에 관한 연구)

  • Lee, Hyung-Jin;Shin, Deok-Ha;Jee, Jeong-Hwan;Baek, Joong-Hwan
    • Proceedings of the KAIS Fall Conference
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    • 2009.12a
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    • pp.961-964
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    • 2009
  • 본 논문은 복합재료로부터 얻어진 C-scan영상에서의 효과적인 잡음 제거에 관한 연구 내용이다. 복합재료에서의 결함을 검출하는 것은 여러 실용, 응용분야에서 관심을 가지는 주제이다. 초음파 영상은 대부분이 육안으로 정확한 판단을 하기에는 어렵고, 잡음의 영향으로 정확한 결함에 대한 영역을 파악하는데 문제를 발생시킨다. 결함의 정확한 판별을 위해서는 물체의 영역을 정확히 판별하는 것이 중요하지만 영상에서 잡음에 대한 문제를 우선 해결해야 한다. C-scan 영상에서의 배경과 결함의 경계영역을 보존하면서 잡음 제거를 위해 웨이브렛(Wavelet) 변환을 이용하는 방법을 제안한다. 특히, C-scan 영상에서 Filtering을 적용하는데에 있어 드비시(Daubechies) Wavelet Filtering이 결함영역에 대한 좀 더 명확한 분석이 가능하게 함을 얘기하고자 한다.

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Droplet Geometry and Its Volume Analysis (기름방울 형상 및 그 체적 분석법)

  • Yoon, Moon-Chul
    • Tribology and Lubricants
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    • v.24 no.6
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    • pp.320-325
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    • 2008
  • The recent industrial application requires technical methods to get the cutting fluid droplet surfaces in particular from the viewpoint of topography and micro texture. To characterize the surface topography of droplet, the combination of the confocal laser scanning microscope (CLSM) and wavelet filtering is well suited for obtaining the droplet geometry encountered in tribological research. This technique indicates a better agreement in obtaining an appropriate droplet surface obtained by the CLSM over a detail range of surface accuracy (resolution: $2{\mu}m$). And the results allow an excellent accuracy in a measurement of a droplet surface. The combination of extended focal depth measurement configured and multi-scale wavelet filtering has proven that it can construct a droplet surface in a successive and accurate way. A multi-scale approach of wavelet filtering was developed based on the decomposition and reconstruction of droplet surface by 2D wavelet transform using db9 (a mother wavelet of daubechies). Also this technique can be extended to characterize the quantification of droplet properties and other field in a wide range of scales. Finally this method is verified to be a better droplet surface modeling in a micro scale arising in a mist machining.