کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
534773 | 870288 | 2012 | 11 صفحه PDF | دانلود رایگان |
Despite the well known advantages that a space-variant representation of the visual signal offers, the required adaptation of the algorithms developed in the Cartesian domain, before applying them in the log-polar space, has limited a wide use of such representation in visual processing applications. In this paper, we present a set of original rules for designing a discrete log-polar mapping that allows a direct application in the log-polar domain of the algorithms, based on spatial multi-scale and multi-orientation filtering, originally developed for the Cartesian domain. The advantage of the approach is to gain, without modifications, an effective space-variance and data reduction. Such design strategies are based on a quantitative analysis of the relationships between the spatial filtering and the space-variant representation. We assess the devised rules by using a distributed approach based on a bank of band-pass filters to compute reliable disparity maps, by providing quantitative measures of the computational load and of the accuracy of the computed visual features.
► A general approach to compute visual features in the log-polar domain.
► A set of design strategies for an optimal discrete log-polar mapping.
► How to effectively exploit the space variance for visual processing.
► A proper choice of the parameters to use existing algorithms without modification.
► Computing the binocular disparity directly in the log-polar domain.
Journal: Pattern Recognition Letters - Volume 33, Issue 1, 1 January 2012, Pages 41–51