Single image dehazing is a fundamental yet challenging task in computer vision. Many studies aim to improve learning-based methods by constructing deep residual networks with multiple small convolutional kernels and attention mechanisms. However, these methods encounter two major limitations. First, small convolutional kernels in redundant layers of deep residual networks may not train effectively, restricting the receptive field’s expansion. Second, haze impacts image information across three dimensions, necessitating consideration of their i...
