Dynamic Pixel Binning in Image Sensors for Motion Detection
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Solution Overview
Problem
Conventional image sensors face challenges in efficiently detecting motion while maintaining high image quality and power efficiency, particularly in applications where high resolution is not always necessary.
Innovation Solution
The implementation of dynamic pixel binning in image sensors, where floating diffusion regions can be selectively enabled or disabled to alternate between different binning configurations, allowing for efficient charge accumulation and detection of motion by comparing pixel values across frames, thereby reducing power consumption and maintaining effective resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If pixel binning is used to reduce resolution, then power consumption is reduced and motion detection is improved, but image quality and spatial coverage are degraded
Solution Approach 1:
The patent implements dynamic pixel binning where the binning configuration is not fixed but can be changed over time. The system alternates between different binning modes (e.g., 2x2 binning, 4x4 binning, or no binning) across successive frames, allowing it to adapt between high-resolution and low-resolution modes based on whether motion detection or image capture is the priority for each frame.
Solution Approach 2:
The system employs periodic alternation between different binning configurations. By cycling through different binning modes in a periodic manner across frames, the system ensures that motion detection benefits from low-resolution binning while image quality benefits from high-resolution frames, achieving both goals over time through periodic switching.
2Productivity
If pixel binning is used to detect motion, then motion detection efficiency is improved, but resolution and spatial coverage are lost
Solution Approach 1:
The system dynamically switches between binning modes that prioritize motion detection and modes that preserve spatial information. By alternating the binning configuration, the system ensures that motion detection efficiency is improved in binning frames while spatial coverage is preserved in non-binning frames, preventing permanent loss of spatial information.
Solution Approach 2:
The system temporarily discards spatial resolution information during binning frames when motion detection is the priority, but recovers this information in subsequent frames by switching to non-binning or less aggressive binning modes. This periodic recovery ensures that spatial coverage information is not permanently lost despite being sacrificed during motion detection frames.
3Measurement precision
If high resolution is maintained for image quality, then image capture quality is improved, but power consumption increases and motion detection efficiency decreases
Solution Approach 1:
The system periodically switches between high-resolution mode (for image quality) and low-resolution binning mode (for power efficiency). This periodic alternation ensures that the system achieves high image quality in designated frames while consuming less power during binning frames, balancing both requirements over time rather than continuously operating at high power consumption.
Solution Approach 2:
The system dynamically adjusts its resolution mode based on operational needs. By making the resolution setting dynamic rather than fixed, the system can switch to power-efficient binning modes when motion detection is sufficient and high image quality is not the immediate priority, thereby reducing overall power consumption while maintaining image quality when needed.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances motion detection efficiency and reduces power consumption by dynamically adjusting pixel binning configurations, allowing for effective image capture and motion detection without sacrificing spatial coverage.
Implementation Method 1
a two-dimensional array of pixel elements... each floating diffusion region corresponding to different one of the pixel elements
Data Source
AI summary
Methods, systems, computer-readable media, and apparatuses for dynamic pixel binning are presented. In one example, an image sensor system includes a plurality of sensor elements; a plurality of floating diffusion regions in communication with the plurality of sensor elements, each floating diffusion region of the plurality of floating diffusion regions configured to be selectively enabled; and at least one comparison circuit coupled to at least two floating diffusion regions of the plurality of floating diffusion regions, the comparison circuit configured to: receive input signals from the two floating diffusion regions, compare the input signals, and output a comparison signal based on the comparison of the input signals.