A Gradient Descent MRI Illumination Correction Algorithm

Magnetic Resonance Images(MRI) are piecewise constant functions that can be corrupted by an inhomogeneous illumination field. We propose a gradient descent parametric illumination correction algorithm for MRI. The illumination bias is modelled as a linear combination of 2D products of Legendre polynomials. The error function is related to the classification error in the bias corrected image. In this work the intensity classes are given beforehand, so the adaptive algorithm is used only to estimate the bias field. We test our algorithm against Maximum A Posteriori algorithms over some images from the ISBR public domain database.