Rambus Binary Pixel technology enables professional-quality images and videos from mobile phone and consumer cameras. The technology includes a breakthrough image sensor and processing architecture that provide single-shot, ultra-high dynamic range (HDR) improved low-light sensitivity and enhanced stop-motion performance.
While the resolution and frame rates supported by mainstream mobile cameras have continued to improve, enhancements in image quality are lagging. High-contrast scenes typical in daily life, such as bright landscapes, sunset portraits, and scenes with both sunlight and shadow, are difficult to capture with today's compact mobile sensors - the range of bright and dark details in these scenes simply exceeds the limited dynamic range of mainstream CMOS imagers.
The Rambus Binary Pixel technology mimics the brilliance of human visual processing by sensing photons using discrete thresholds similar to the rods and cones of the human eye. This "binary operation" creates dramatically better videos and photos from mobile and consumer devices that include the full gamut of details in dark and bright intensities. The complete scene data enables more creative post-processing and color enhancement capabilities resulting in more "keeper" images and videos that showcase life as it was meant to be seen. Furthermore, Binary Pixel processing improves low-light capture and enhances stop-motion performance for dramatically sharper images of moving objects.
Binary Pixel technology builds upon the visionary works of imaging and signal processing experts including: The Gigavision Camera by Professor Martin Vetterli at École polytechnique fédérale de Lausanne (EPFL) and Professor Edoardo Charbon at Delft University of Technology (TU Delft) & EPFL; The Digital Film Sensor by Dr. Eric Fossum, pioneer in the modern CMOS active pixel image sensor. Rambus engineers are collaborating with these experts to bring binary pixel inventions to market.
|Binary Operation||Binary operation enables the imagers to sense photons using discrete thresholds, similar to the human eye, for better sensitivity across the gamut of dark to bright and improved dynamic range.|
|Spatial Oversampling||Spatial oversampling sub-divides Individual pixels to capture more data and extend dynamic range of the imager.|
|Variable Temporal Oversampling||Variable temporal oversampling takes multiple samples during a single exposure period to avoid pixel saturation improving the sensor's signal-to-noise ratio and low-light performance for better indoor and nighttime photography.|