Software-Defined Imaging: A Survey

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.

Automated summary

Huge advancements have been made in modern image-sensing hardware and visual computing algorithms. However, there is still a gap between hardware and software design in imaging systems, which limits collaboration between research domains. This survey explores existing works that use software-defined imaging (SDI) to replace conventional hardware components, allowing users to program image sensors according to their needs. The scope of the survey covers various imaging systems and discusses the components and future research directions of SDI.