For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/07/optimized-image-processing-for-automotive-image-sensors-with-novel-color-filter-arrays-a-presentation-from-nextchip/
Young-Jun Yoo, Vice President of the Automotive Business and Operations Unit at Nextchip, presents the “Optimized Image Processing for Automotive Image Sensors with Novel Color Filter Arrays” tutorial at the May 2023 Embedded Vision Summit.
Traditionally, image sensors have been optimized to produce images that look natural to humans. For images consumed by algorithms, what matters is capturing the most information. We can achieve this via higher resolution, but higher resolution means lower sensitivity. To increase resolution and maintain high sensitivity, color information can be sacrificed—but in automotive applications, color is critical. In response, suppliers offer image sensors that capture color information using novel color filter arrays (CFAs).
Instead of the traditional RGGB array, these sensors use patterns like red-clear-clear-green (RCCG). These approaches yield good results for perception algorithms, but what about cases where images are used by both algorithms and humans? Can we reconstruct a natural-looking image from an image sensor using a non-standard CFA? In this talk, Yoo explores novel CFAs and introduces Nextchip’s vision processor, which supports reconstruction of natural-looking images from image sensors with novel CFAs, including RGB-IR sensors.
6. 6
Key factor of machine vision
<Ref. Basler “High-Sensitivity Image Processing Cameras”>
• High sensitivity is the key factor of machine vision for achieving a quality video image with low image noise even
in poor lighting conditions.
• The higher the signal-to-noise ratio, the better the object can be detected.
• Sensitivitiy is more important than color in machine vision.
<Ref. gla.ac.uk “Sensitivity and noise”>