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

To remove spike noise in the scanning laser microscopic image of diamond abrasive grain without blurring the sharp edges, a new smoothing technique that combines a conventional averaging technique with wavelet transforms is proposed. The diamond abrasive grain image 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 spike noise points are extracted. A conventional averaging technique is then applied to the same points in the original image as the spike noise points in the high-frequency image. The smoothing technique successfully removes both clustered and unclustered spike noise while preserving the sharp edges. Spike noise is removed without a loss in the original grain shape. This smoothing technique will surely be effective for other applications.