A fast filter enhancement method for the infrared image
Wei Qi, Dongjing Wang, Wei Li · 2020
Recent advances in image enhancement explored the power of convolutional neural network (CNN) to achieve a better performance. Despite the great success of CNN-based methods, it is not easy to apply these methods to edge devices (such as FPGA, ASIC) due to the requirement of heavy computation, and the CNN-based methods heavily rely on the training datasets. In this paper, we propose a simple method for image enhancement, without any training steps.