NDLI: Speckle Reducing Anisotropic Diffusion Based on Directions of Gradient

Content Provider	IEEE Xplore Digital Library
Author	Hye Suk Kim Keon Hee Park Hyo Sun Yoon Guee Sang Lee
Copyright Year	2008
Description	Author affiliation: Dept. of Comput. Sci., Chonnam Nat. Univ., Gwangju (Hye Suk Kim; Keon Hee Park; Hyo Sun Yoon; Guee Sang Lee)
Abstract	In this paper, we focus on the problem of speckle removal and edge preservation by means of anisotropic diffusion in ultrasound images. The conventional anisotropic diffusion is performed in four directions (north, south, east, west) without condition in the previous methods (Perona and Malik, 1990; Black et al., 1998 ; and Hae Yong Kim, 2006). In this paper, a new anisotropic diffusion method based on directions of gradient is proposed. At first, is calculated by using GHAD (gradient hostogram-based anisotropic diffusion) for anisotropic diffusion. Secondly, Prewitt mask is performed for the magnitude of gradient and directions of gradient. As a result, when the magnitude of gradient is large enough, the pixel is considered as the edge. In the case of edge, the weight of diffusion is selected adaptively according to the directions of gradient. Otherwise, the proposed diffusion is performed at 8-directions (north, south, east, west, north_left, north_right, south_left, south_right) which are not an edge. Experiments results show that the proposed method can eliminate noise/speckle and can remain contour of edge in ultrasound images with speckle noises.
Starting Page	198
Ending Page	203
File Size	255480
Page Count	6
File Format	PDF
ISBN	9780769532738
DOI	10.1109/ALPIT.2008.88
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-07-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	speckle Anisotropic magnetoresistance Ultrasonic imaging Image edge detection Noise Speckle anisotropic diffusion gradinet Pixel Equations
Content Type	Text
Resource Type	Article

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