Computer Vision Talks at Columbia University

Blind Removal of Image Non-Linearities

Hany Farid

Department of Computer Science, Dartmouth College

Friday, November/16, 12 Noon

CS Conference Room, 4th floor, MUDD 

Host: Prof. Shree Nayar 

Abstract 

Most imaging devices introduce luminance non-linearities (e.g.,gamma correction). For many applications in image processing and computer vision it is advantageous to remove these non-linearities prior to subsequent processing. I will present a technique for blindly removing luminance non-linearities in the absence of any calibration information or explicit knowledge of the imaging device. The basic approach exploits the fact that a non-linearity introduces specific higher-order correlations in the frequency domain (beyond second-order). These correlations can be detected using tools from polyspectral analysis. The non-linearities can then be estimated and removed by simply minimizing these correlations. I will also show applications to the blind removal of lens distortions.