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Irida Labs’ NoiseSweeper and EnLight Software Now Available on Cadence Tensilica Imaging/Vision DSPs

SAN JOSE, Calif., 23 Aug 2016 – Cadence Design Systems, Inc. (NASDAQ: CDNS) and Irida Labs announced that Irida Labs’ IRIS-EnLight and IRIS-NoiseSweeper technologies are now available on the Cadence® Tensilica® Vision family of digital signal processors (DSPs). Developed by vision industry experts at Irida Labs, these new technologies enable mobile, automotive, home electronics and wearables designers to achieve improvements in performance while using less power compared with common CPU and GPU implementations. Measurements indicate at least ten times lower power consumption compared to a CPU implementation and five times lower power consumption compared to a GPU implementation. For more information, visit http://www.cadence.com/go/irida-labs.

Irida Labs’ IRIS-EnLight low-light video software enhances videos and images taken in challenging lighting conditions and slow shutter speeds. The software enhances the image and video contrast and intensity to restore the original color content of the scene. It also features a scheme that reduces noise resulting from low-light perception of the image sensor.

In addition, IRIS-NoiseSweeper software has also been ported to the Tensilica Vision DSP to provide premium video quality and cleaner still-images. The software is targeted at image noise reduction for high-resolution still images. The technology features an automated noise profile estimation that reduces calibration needs and shortens development time. It operates in a single frame and eliminates any motion-blurring phenomena associated with multi-frame techniques. For more information on Irida Labs’ technologies, visit http://www.iridalabs.gr/products.

The Tensilica family of imaging/vision DSPs was designed for the complex algorithms in imaging, video and computer vision applications including innovative multi-frame image capture, video pre- and post-processing, object and face recognition, low-light enhancement and many other complex tasks.

“Embedded vision and machine learning is becoming more and more popular in a number of different markets like mobile, automotive and surveillance. The wide adoption of embedded vision depends on the use of computationally complex algorithms in challenging low-power environments,” said Vassilis Tsagaris, CEO of Irida Labs. “Our partnership with Cadence enables us to deliver high-performance power-efficient computer vision solutions to the market, and is also very promising for our machine-learning -based visual perception solutions.”

?About Cadence

Cadence enables global electronic design innovation and plays an essential role in the creation of today’s integrated circuits and electronics. Customers use Cadence software, hardware, IP and services to design and verify advanced semiconductors, consumer electronics, networking and telecommunications equipment, and computer systems. The company is headquartered in San Jose, Calif., with sales offices, design centers and research facilities around the world to serve the global electronics industry. More information about the company, its products and its services is available athttp://www.cadence.com.

About Irida Labs

Irida Labs (Patras, Greece) is a computer vision and machine learning technology company focused on bridging the gap between cameras and the human eye by bringing visual perception to any device. We develop software products using sophisticated image processing and machine learning techniques. Through the use of heterogeneous programming methods, our solutions are applicable to any CPU, GPU or DSP/ASP platform or combinations thereof. Our product and technology portfolio delivers innovative, optimized computer vision solutions while being mindful of power consumption, memory constraints and processing speed for a diverse set of applications including mobile devices, action cameras, drones, automotive systems, surveillance systems and industrial and robotic vision systems. Please visit iridalabs.com http://www.iridalabs.gr/ for more information.

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