Edges as Outliers: Anisotropic Smoothing Using Local Image Statistics
SCALE-SPACE '99 Proceedings of the Second International Conference on Scale-Space Theories in Computer Vision
Fast rigid registration of vascular structures in IVUS sequences
IEEE Transactions on Information Technology in Biomedicine - Special section on body sensor networks
A Model for Radar Images and Its Application to Adaptive Digital Filtering of Multiplicative Noise
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Enhancement and Noise Filtering by Use of Local Statistics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Speckle reducing anisotropic diffusion
IEEE Transactions on Image Processing
Contour detection based on nonclassical receptive field inhibition
IEEE Transactions on Image Processing
Oriented Speckle Reducing Anisotropic Diffusion
IEEE Transactions on Image Processing
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In this paper, a new operator for contour detection in images with multiplicative noise is presented. Traditional methods of edge detection, as those based in gradient operator or measures of variance, follow a logic and a math formulation in correspondence with the Differential and Integral Calculus of Newton. This work presents a new operator of non-Newtonian type which had shown be more efficient in contour detection than the traditional operators. Like the regular gradient, a non-Newtonian gradient can be used in a number of more complex methods, which shows its potential in the contours detection in images affected by multiplicative noise.