%0 Journal Article %T A Novel Space Variant Image Representation %A Naveen Onkarappa %A Angel Sappa %J Journal of Mathematical Imaging and Vision %D 2013 %V 47 %N 1-2 %I Springer US %@ 0924-9907 %F Naveen Onkarappa2013 %O ADAS; 600.055; 605.203; 601.215 %O exported from refbase (http://refbase.cvc.uab.es/show.php?record=2243), last updated on Thu, 21 Jan 2016 12:30:47 +0100 %X Traditionally, in machine vision images are represented using cartesian coordinates with uniform sampling along the axes. On the contrary, biological vision systems represent images using polar coordinates with non-uniform sampling. For various advantages provided by space-variant representations many researchers are interested in space-variant computer vision. In this direction the current work proposes a novel and simple space variant representation of images. The proposed representation is compared with the classical log-polar mapping. The log-polar representation is motivated by biological vision having the characteristic of higher resolution at the fovea and reduced resolution at the periphery. On the contrary to the log-polar, the proposed new representation has higher resolution at the periphery and lower resolution at the fovea. Our proposal is proved to be a better representation in navigational scenarios such as driver assistance systems and robotics. The experimental results involve analysis of optical flow fields computed on both proposed and log-polar representations. Additionally, an egomotion estimation application is also shown as an illustrative example. The experimental analysis comprises results from synthetic as well as real sequences. %K Space-variant representation %K Log-polar mapping %K Onboard vision applications %U http://dx.doi.org/10.1007/s10851-012-0384-5 %P 48-59