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Combining an ISP and Vision Processor to Implement Computer Vision

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An ISP (image signal processor) in combination with one or several vision processors can collaboratively deliver more robust computer vision processing capabilities than vision processing is capable of providing standalone. However, an ISP operating in a computer vision-optimized configuration may differ from one functioning under the historical assumption that its outputs would be intended for human viewing purposes. How can such a functional shift be accomplished, as well as handling applications in which both computer vision and human viewing functions require support? This article discusses the implementation options involved in heterogeneously leveraging an ISP and one or more vision processors to efficiently and effectively execute both traditional and deep learning-based computer vision algorithms.

ISPs, whether in the form of a standalone IC or as an IP core integrated into a SoC or image sensor, are common in modern camera-inclusive designs (see sidebar "ISP Fundamentals"). And vision processors, whether to handle traditional- or deep learning-based algorithms, or a combination of the two, are increasingly common as well, as computer vision adoption becomes widespread. Sub-dividing the overall processing of computer vision functions among the collaborative combination of an ISP and vision processor(s) is conceptually appealing from the standpoint of making cost-effective and otherwise efficient use of all available computing resources.

However, ISPs are historically "tuned" to process images intended for subsequent human viewing purposes; as such, some ISP capabilities are unnecessary in a computer vision application, while others are redundant with their vision processor-based counterparts and the use of others may actually be detrimental to the desired computer vision accuracy and other end results. The situation is complicated even further in applications where an ISP's outputs are used for both human viewing and computer vision processing (see sidebar "Assessing ISP Necessity").

This article discusses the implementation options involved in combining an ISP and one or more vision processors to efficiently and effectively execute traditional and/or deep learning-based computer vision algorithms. It also discusses how to implement a design that handles both computer vision and human viewing functional requirements. It provides both general concept recommendations and detailed specific explanations, the latter in the form of case study examples. And it also introduces readers to an industry alliance created to help product creators incorporate vision-enabled capabilities into their SoCs, systems and software applications, along...