Effective image post-processing algorithms are vital for the successful direct imaging of exoplanets. Existing algorithms use techniques based on a low-rank approximation to separate the rotating planet signal from the quasi-static speckles. In this paper, we present a novel approach that iteratively finds the planet’s flux and the low-rank approximation of quasi-static signals, strengthening the existing model based on lowrank approximations. We implement the algorithm with two different norms and test it on data, showing improvement over classical low-rank approaches. Our results highlight the benefits of iterative refinement of low-rank approximation to enhance planet detection.