Seminar: Two Simple Unfolded Residual Networks for Single Image Dehazing

Summary: Haze is an environmental factor that impairs visibility for outdoor imaging systems, presenting challenges for computer vision tasks. In this paper, we propose two novel approaches that combine the classical dark channel prior with variational formulations to construct an energy functional for single-image dehazing. The proposed functional is minimized using a proximal gradient descent scheme, which is unfolded into two different networks: one built with residual blocks and the other with residual channel attention blocks. Both methods provide straightforward yet effective solutions for dehazing, achieving competitive results with simple and interpretable architectures.