Spike noise removal in the scanning laser microscopic image of diamond abrasive grain using a wavelet transform

Kitami Institute of Technology, Notsukeushi, Hokkaidō, Japan
Optics Communications (Impact Factor: 1.45). 10/2002; 211(1-6):73-83. DOI: 10.1016/j.optcom.2004.05.056


To remove spikenoise in the scanninglasermicroscopicimage of diamondabrasivegrain without blurring the sharp edges, a new smoothing technique that combines a conventional averaging technique with wavelettransforms is proposed. The diamondabrasivegrainimage is decomposed into high- and low-frequency subimages using wavelet filters, and all subimages except the lowest frequency one are synthesized to obtain a high-frequency image, from whose pixel values spikenoise points are extracted. A conventional averaging technique is then applied to the same points in the original image as the spikenoise points in the high-frequency image. The smoothing technique successfully removes both clustered and unclustered spikenoise while preserving the sharp edges. Spikenoise is removed without a loss in the original grain shape. This smoothing technique will surely be effective for other applications.

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    • "In the last times there is also an increasing interest of using Wt to detect spikes from signals [38] [42] [43]. For example, Ehrentreich et al. [38] proposed Daubechies, Symlet and Coiflet wavelet families as the most suitable for Raman spike de-noising. "
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