Total Variation Minimization: A Regularized Restoration Method for Image Detail Preservation

In image restoration techniques, Total Variation (TV) minimization serves as a regularization-based recovery method designed to preserve image details. This algorithm implements an alternating minimization strategy with precise iterations to simultaneously restore both the image and point spread function. Code implementation typically involves solving partial differential equations using gradient descent or primal-dual optimization methods. Experimental results demonstrate robust image restoration even under high-noise conditions, with key functions handling edge-preserving regularization and noise suppression.