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cameras with complementary optical properties tied to an A16 chip that embeds a CPU, GPU, an image processor, and a neural engine. In addition to functionality benefits, today’s miniaturised imaging systems offer cost, weight, and packaging size advantages together with the possibility to interpret the content to make decisions, over traditional standalone optical systems. Moreover, the continuing
evolution of AI-based technologies in computational imaging – such as the development of neural networks – is revealing their potential to supplement or even replace traditional ISPs. This evolution will support more complex features like advanced denoising, low-light enhancement, blur reduction, and wide dynamic ranges to further improve image quality.” As with any new technology,
with the benefits also come the challenges of integrating today’s miniaturised and digitised imaging systems. These are often related to
balancing performance with power and area, where power could include thermal issues and area directly impacts cost. Cooper says: “Adding AI to imaging systems – which brings many advantages – aggravates the performance, power, area (PPA) challenges. Implementing convolutional neural networks (CNNs) for vision requires a significant amount of computations and therefore a significant amount of data movement (of both sensor data and coefficients) which, in turn, increase the power consumption. Every imaging application will need to balance the benefits of adding AI with the cost of adding the resources for those benefits.”
Paving the way for computational imaging To help overcome such challenges and realise the potential of computational imaging, a system-level analysis of imaging systems is essential. Synopsys offers a comprehensive suite of solutions that cater to the entire
imaging pipeline. Cooper says: “For companies implementing imaging systems, there are three key benefits of partnering with Synopsys. The first is our range of software tools – from EDA tools, to lens design, to system level analysis, to analysing neural network performance, and more, we can help design, analyse and implement imaging systems-on- chip (SoCs). Second, Synopsys has a broad range of licensable IP that allows companies to prioritise their designers’ efforts on differentiating technology while licensing standard IP blocks from a trusted provider. Licensing Synopsys’s ARC NPX6 Neural Processing Unit IP speeds time to market but avoids designing a customer neural network engine and the software tools to support that engine.” The third way Synopsys can help customers, says Viasnoff, is its market expertise: “Want to add an imaging system in an automotive application, for example? Synopsys has helped many companies in this area
and can share best practices and point out potential pitfalls.”
A bright future As computational imaging continues to evolve, it is likely that more powerful and affordable imaging systems will evolve that cater to diverse domains, from assisted driving systems to mixed-reality applications. Also, the inclusion of AI into the imaging pipeline will likely accelerate. Cooper concludes: “Convolutional Neural Networks – the standard for vision applications for 10 years – are being challenged by transformers. Transformers, the neural networks that generative AI are based on, improve accuracy but at the cost of even more computations and data movement. As more imaging pipelines include AI, there is a greater opportunity to break down the silos between lens design and processing of the data in the ISP or neural network engine. This will require more integrated toolchains and system-level analysis tools.”
New White Paper Now Online
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Computational imaging craves system-level design and simulation tools to leverage disruptive AI in embedded vision
In this paper, Synopsys reviews market trends and analyses promising system co-design and co-optimisation approaches that unleash the full potential of computational imaging systems by decreasing hardware complexity while keeping computing requirements at a reasonable level.
www.electrooptics.com/white-papers
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