Daytime Color Image

Daytime color image processing is a vibrant research area focusing on improving image quality, analysis, and applications. Current efforts concentrate on addressing challenges like raindrop removal, translating infrared images to daytime color for enhanced perception, and accurately estimating industrial growth from high-resolution imagery using techniques like Mask R-CNN and convolutional neural networks. These advancements are significant for various applications, including improving image recognition in edge caching systems, enhancing computer vision tasks, and providing valuable insights for monitoring economic development and environmental changes.