Optical Engineering • Open AccessIterative adaptive hybrid image restoration for fast convergence
We present an iterative adaptive hybrid image restoration algorithm for fast convergence. The local variance, mean, and maximum values are used to constrain the solution space. These parameters are computed at each iteration step using a partially restored image at each iteration, and they are used to impose the degree of local smoothness on the solution. The resulting iterative algorithm exhibits increased convergence speed and better performance than typical regularized constrained least-squares approach.