Integrating Gstreamer with Xilinx's ZCU 104 Edge Platform for Real-Time Intelligent Image Enhancement

Edge computing is becoming very popular. Many researchers are using edge devices for computing artificial intelligence, especially in real-time applications of computer vision by the use of Convolutional Neural Networks (CNNs). Edge devices can encounter non-ideal environments that impact the effectiveness of a CNN model's predictions. We propose a tool flow methodology for implementing a real-time intelligent image enhancement technique for deploying and validating CNNs on edge devices. In this work, we implement this proposed methodology in a modular and user-friendly way. We show that this methodology is capable of real-time intelligent image enhancement on various CNN models.