SAN JOSE, Calif., January 5, 2017—Cadence Design Systems, Inc. (NASDAQ: CDNS) today announced that Almalence, a leader in computational imaging, has collaborated with Cadence to port their Video SuperSensor video image quality improvement software to the Cadence® Tensilica® Vision DSP. Almalence Video SuperSensor software is a groundbreaking technology that now, when combined with the vision processing power of the Tensilica Vision DSP, can make image quality improvements at video framerates, previously only achievable on still images. Video SuperSensor can simultaneously improve resolution, low light sensitivity and dynamic range without any changes to the camera hardware and is ideal for battery-powered embedded platforms such as mobile, drone, and augmented and virtual reality (AR/VR) devices.
Tensilica Vision DSPs provide the necessary power and performance for running complex imaging algorithms very efficiently, with lower power consumption and higher performance. After being ported to the Tensilica Vision DSP, Almalence Video SuperSensor was tested and shown to achieve up to 10X more performance in regards to frames per second with the Vision DSP over the use of a CPU and GPU alone, which lack the power and computational efficiency to run complex imaging software at 1080p frame rates inside practical battery and thermal constraints.
“We have experienced a very successful collaboration with the Cadence Tensilica team. The SIMD VLIW architecture of the Vision DSP enabled us to achieve a very efficient implementation of our Video SuperSensor software in a very short time,” said Eugene Panich, CEO at Almalence. “Due to the excellent software development tools and imaging library support provided by Cadence, it was remarkably fast and easy to port our software.”
“The form factor of mobile devices has made it very difficult until now to provide high-quality zoom in a low-light environment,” said Dino Bekis, vice president product marketing for the IP group at Cadence. “The combination of the Video SuperSensor software from Almalence and the Tensilica Vision DSP enables a highly efficient solution for battery-powered devices that significantly improves the user experience.”
The Tensilica Vision DSP family is designed for demanding imaging, computer vision and convolutional neural network applications in the mobile, automotive, surveillance, gaming, drone, and wearable markets. Comprised of two products, the Vision P5 DSP and the Vision P6 DSP, the Vision DSP family establishes a new standard in high-performance, low-energy digital signal processing.
Visit Cadence at CES 2017 to see the complete solution. For more information about Cadence at CES 2017, visit www.cadence.com/content/cadence-www/global/en_US/home/company/events/industry-events/ces-2017.html.
For more information about the Tensilica Vision DSP family, visit http://ip.cadence.com/ipportfolio/tensilica-ip/image-vision-processing?CMP=pr050216_VisionP6.
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 at www.cadence.com.
Almalence is the global leader in computational imaging technologies, used in a wide range of optical systems, from high-end DSLR cameras to mobile phones. Almalence's solutions are licensed by top smartphone OEMs and shipping on more than 30M devices annually. Almalence, Inc. is a privately owned company with headquarters in Austin, Texas and the team distributed across the world - USA, Russia, Israel, China and South Korea. For more information on Almalence technologies and Video SuperSensor please visit www.almalence.com.