A novel dictionary learning-based algorithm for online reconstruction of dynamic MR images is proposed. The algorithm consists of both patch-based (local) and global sparsity terms. The group patching is employed to classify the patches based on their similarities. A modified dependent hierarchical beta process (dHBP) is utilized as the prior for the dictionary learning process.