This webinar explores key challenges associated with CMOS image sensor verification and introduces industry-proven solutions and methodologies to address them.
CMOS images sensors (CIS) are now the preferred image sensor across various markets due to the ultra-compact size, high resolution, faster frame rates, low power consumption, and low fabrication cost. Mobile phones, being one of the biggest drivers of demand, now average three cameras per phone and are expected to average four within the next three years. The latest advanced driver-assistance systems (ADAS), in the automotive market, are fueling the need for more sensors including backup cameras, 360-degree surround view, video mirrors, and driver monitoring. Medical imaging is not far behind, with growing demand for specialized image sensors for surgical and other bio-medical applications.
Verification of CMOS image sensors (CIS) is challenging on multiple levels as they contain large arrays of pixels and replicated circuits. CIS have extremely sensitive signal chains, affected by non-uniformities at both the local and global level. Noise is often cited as the most challenging aspect as it impacts the visible quality of an image. Noise along with other factors must also account for variability due to process, voltage, and temperature variation. Image quality and robustness are the key requirements to win market share across various applications. CIS verification requires comprehensive block-level characterization for accurate noise analysis and top-level verification to ensure performance and power specs are met in silicon. This webinar will cover some key challenges associated with CMOS Image sensor verification and introduce industry-proven solutions and methodologies to address them.
What you will learn:
CMOS image sensor trends and verification challenges
Methods and tools to correlate Simulation-to-Silicon using Mentor’s
How to address CIS mixed-signal verification with Mentor Symphony
How to perform variation-aware design and verification of CIS with Mentor Solido Variation Designer