X-NET For Single Image Raindrop Removal
Jiamin Lin, Longquan Dai · 2020
Photos taken on rainy days are likely degraded by raindrops adhered to camera lenses. Removing raindrops from images is a tough task. Its difficulties lie in restoring high frequency information from corrupted images while keeping the color of restored images consistent with human perception. To solve these problems, we propose an end-to-end convolutional neural network consisting of X-Net and RAD-Net (Raindrop Automatic Detection Net). X-Net takes advantage of Long Skip Connections and Cross Branch Connections to generate raindrop-free image with enough details. RAD-Net assists X-Net to produce better results by yielding raindrop location. Extensive experiments show our approach outperforms state-of-the-art methods quantitatively and qualitatively.