Gradient domain contrast enhancement with histogram-guided boundary conditions
A novel contrast enhancement algorithm with histogram-guided boundary conditions is proposed in this work. The proposed algorithm enhances details in local regions by boosting gradient components, while improving the overall contrast by imposing boundary conditions based on a global transformation function. Moreover, we develop an efficient masking scheme, called the soft masking, to strike the balance between the global enhancement and the local enhancement. Simulation results demonstrate that the proposed algorithm can yield high quality output images by improving both global and local contrast simultaneously.