ISP Meets Deep Learning: A Survey on Deep Learning Methods for Image Signal Processing

IF 23.8 1区计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS

ACM Computing Surveys Pub Date : 2024-12-19 DOI:10.1145/3708516

Claudio Filipi Goncalves dos Santos, Rodrigo Reis Arrais, Jhessica Victoria Santos da Silva, Matheus Henrique Marques da Silva, Wladimir Barroso Guedes de Araujo Neto, Leonardo Tadeu Lopes, Guilherme Augusto Bileki, Iago Oliveira Lima, Lucas Borges Rondon, Bruno Melo de Souza, Mayara Costa Regazio, Rodolfo Coelho Dalapicola, Arthur Alves Tasca

引用次数: 0

Abstract

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(DL) 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.

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ISP与深度学习：图像信号处理的深度学习方法综述

相机的整个图像信号处理器（ISP）依赖于几个处理过程来转换来自彩色滤波阵列（CFA）传感器的数据，如去马赛克、去噪和增强。这些过程可以通过硬件或软件执行。近年来，深度学习（Deep Learning，DL）作为一种解决方案出现了，它可以解决其中一些问题，甚至可以用一个神经网络取代整个 ISP 来完成任务。在这项工作中，我们调查了这一领域最近的几项研究，并对它们进行了深入分析和比较，包括结果和可能的改进点，供未来的研究人员参考。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

ACM Computing Surveys 工程技术-计算机：理论方法

CiteScore

33.20

自引率

0.60%

发文量

372

审稿时长

12 months

期刊介绍： ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.