Software-Defined Imaging: A Survey
Software-Defined Imaging: A Survey
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DOI：
10.1109/jproc.2023.3266736
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发表时间：
2023-05
影响因子：
20.6
通讯作者：
Suren Jayasuriya;Odrika Iqbal;Venkatesh Kodukula;Victor Torres;R. Likamwa;A. Spanias
中科院分区：
文献类型：
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作者：
Suren Jayasuriya;Odrika Iqbal;Venkatesh Kodukula;Victor Torres;R. Likamwa;A. Spanias
多年来，就现代图像感应硬件和视觉计算算法（例如，计算机视觉，图像处理和计算摄影）而取得了巨大进步。成像系统中的软件设计，一个丝绸从另一个差异弥散该差距。检查和机器人技术。适合最终应用程序。调查涵盖单像捕获，多图像和爆发摄影的成像系统以及视频。最后，我们概述了SDI系统的基础架构和资源，我们还讨论了该领域的未来研究方向。
Huge advancements have been made over the years in terms of modern image-sensing hardware and visual computing algorithms (e.g., computer vision, image processing, and computational photography). However, to this day, there still exists a current gap between the hardware and software design in an imaging system, which silos one research domain from another. Bridging this gap is the key to unlocking new visual computing capabilities for end applications in commercial photography, industrial inspection, and robotics. In this survey, we explore existing works in the literature that can be leveraged to replace conventional hardware components in an imaging system with software for enhanced reconfigurability. As a result, the user can program the image sensor in a way best suited to the end application. We refer to this as software-defined imaging (SDI), where image sensor behavior can be altered by the system software depending on the user’s needs. The scope of our survey covers imaging systems for single-image capture, multi-image, and burst photography, as well as video. We review works related to the sensor primitives, image signal processor (ISP) pipeline, computer architecture, and operating system elements of the SDI stack. Finally, we outline the infrastructure and resources for SDI systems, and we also discuss possible future research directions for the field.