

Author: Sethi Dave I. Sims Mohammad-Reza Siadat Ishwar K.
Publisher: Inderscience Publishers
ISSN: 1752-9131
Source: International Journal of Computational Vision and Robotics, Vol.2, Iss.3, 2011-10, pp. : 266-276
Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.
Abstract
Spatial image filtering is a method by which an image can be enhanced. The method involves computing correlation of a mask and input image to produce desired image. This requires a number of computations consisting of addition and division operations. Such operations are repeated multiple times for common areas of overlapping masks as we shift the mask over consecutive pixels. As a result, there is a significant number of redundant operations that slows down the spatial filtering process. In this paper, we propose a new method to eliminate redundant operations and we apply it to volumetric MRI images using mean filter. We analyse the complexity of the proposed method and compare its processing speed to that of the conventional implementation of the mean filter. Our method shows up to one order of magnitude improvement in processing speed over the conventional method especially on 3D images with large filter masks.
Related content




Spatial Filtering Using the Active-Space Indexing Method
Graphical Models, Vol. 63, Iss. 3, 2001-05 ,pp. :



