The entire Image Signal Processor (ISP) of a camera relies on several processes to transform the data from the Color Filter Array (CFA) sensor, such as demosaicing, denoising, and enhancement. These processes can be executed either by some hardware or via software. In recent years, Deep Learning has emerged as one solution for some of them or even to replace the entire ISP using a single neural network for the task. In this work, we investigated several recent pieces of research in this area and provide deeper analysis and comparison among them, including results and possible points of improvement for future researchers.

翻译：相机的完整图像信号处理器依赖多个过程来转换来自颜色滤波阵列传感器的数据，例如去马赛克、去噪和增强。这些过程既可以通过硬件执行，也可以通过软件实现。近年来，深度学习已成为其中某些过程的解决方案，甚至可以用单一神经网络取代整个图像信号处理器。在本研究中，我们调研了该领域近期多项研究，并对其进行了深入分析与比较，包括研究结果及未来研究者可能的改进方向。