A novel algorithm to estimate illumination parameter based on quotient image(QI)is proposed to improve the accuracy of facial image illumination synthesis. Analysis indicates that the hypothesis of uniform albedos in traditional QI algorithm can not be strictly hold
and that inherent error in illumination parameter estimation will be incurred. Then
an improved objective function is derived in the parametric illumination subspace framework
and the albedo ratios is replaced by the quotient image itself
so that the impacts of the hypothesis is weakened
and independent albedo per facial pixel can be permitted. An iterative algorithm is designed to solve the objective function through linear system
and illumination parameter can be estimated at high accuracy. Experiments on the oriental face database(OFD)and the AI&R face database show that the proposed algorithm has good convergence ability
and that the trace ratio for illumination estimation and the peak-signal-to-noise-ratio in illumination synthesis images are improved by 25.49~43.09 dB and 4.51~9.24 dB
respectively.
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references
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