Multi-Objective Optimization Approach to Ill-Posed Inverse Problem

Influenced by ill-posedness, the solution of inverse problems is usually unstable, not unique or does not exit. One of the characteristics which image reconstruction differs from other inverse problems is that the former emphasizes not only the solution accuracy, but also its fidelity based on various visual features. Multi-objective optimization approach, a new approach to solve the ill-posed inverse problems in image reconstruction, was presented with its theoretical basis and the experiment results. Relationship between the accuracy and weighted coefficients of each single objective function was discussed with a set of test data.