Programmable Image Sensor ROI Control for Power and Frame Rate
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional image sensors lack dynamic control over pixel cell operations, leading to inefficient power consumption, bandwidth usage, and limited performance in generating high-resolution images and high frame rates, especially in mobile devices where resources are constrained.
Innovation Solution
An integrated system comprising an image sensor, an image processor, and a controller within a semiconductor package, where the controller dynamically programs the image sensor based on image data to optimize power, resolution, and frame rate by identifying regions of interest and adjusting pixel cell operations, using techniques like neural networks for feature extraction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all pixel cells operate at full resolution and frame rate, then image quality is maintained, but power consumption increases and processing efficiency decreases
Solution Approach 1:
The patent divides the pixel array into multiple regions with different operational characteristics. Specifically, it segments the sensor into regions of interest (ROI) and non-ROI areas, allowing differential control of pixel operations. This segmentation enables high-resolution capture only where needed while reducing power consumption in other areas.
Solution Approach 2:
The patent implements local quality by applying different operational modes to different spatial regions of the sensor. Pixels within the ROI maintain full resolution and frame rate, while pixels outside the ROI operate at reduced resolution or are disabled. This local differentiation optimizes the balance between image quality and power consumption based on scene requirements.
2Loss of information
If all pixel cells process and output data at high resolution, then data detail is preserved, but data processing load increases
Solution Approach 1:
The patent extracts only the necessary data from the pixel array by identifying and isolating regions of interest. Instead of processing all pixel data uniformly, the system extracts and processes only data from ROI pixels at full resolution, while subsampling or discarding data from non-ROI pixels. This extraction approach preserves critical information while reducing overall processing load.
Solution Approach 2:
The patent applies partial action by processing only a subset of pixel data at full resolution rather than all pixels. The system dynamically determines which pixels require full processing based on scene analysis, applying full-resolution processing only where necessary and reduced processing elsewhere, thereby optimizing the trade-off between information preservation and processing efficiency.
3Speed
If the image sensor operates at maximum frame rate, then temporal resolution is improved, but power consumption and processing demands increase
Solution Approach 1:
The patent implements dynamic operation by allowing the sensor to adjust its frame rate and resolution characteristics in real-time based on scene requirements. The system dynamically switches between different operational modes (e.g., full resolution/high frame rate for active targets, reduced resolution/lower frame rate for static scenes) to optimize power consumption while maintaining necessary temporal resolution.
Solution Approach 2:
The patent employs periodic scanning or sampling strategies where the sensor alternates between high-frame-rate capture of ROI and lower-frame-rate capture of non-ROI areas. This periodic differentiation allows the system to maintain high temporal resolution for important regions while reducing overall power consumption through lower sampling rates in other areas.
4Adaptability or versatility
If pixel-level programming control is implemented, then operational flexibility is improved, but device complexity increases
Solution Approach 1:
The patent achieves operational flexibility through a universal control architecture that manages multiple pixel regions with different requirements using a single programmable controller. The controller can dynamically configure any pixel or group of pixels to operate in various modes (full resolution, reduced resolution, disabled) based on scene demands. This multi-functional control approach provides adaptability without requiring separate dedicated circuits for each operational mode.
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 the performance of imaging systems by reducing power consumption and bandwidth usage, improving image quality and processing speed, and reducing latency, particularly in applications like augmented and virtual reality.
Implementation Method 1
Each pixel cell may include a photodiode to sense light by converting photons into charge (e.g., electrons or holes)
Data Source
AI summary
In one example, an apparatus comprises: an image sensor comprising an array of pixel cells, each pixel cell including a photodiode and circuits to generate image data, the photodiodes formed in a first semiconductor substrate; and a controller formed in one or more second semiconductor substrates that include the circuits of the array of pixel cells, the first and second semiconductor substrates forming a stack and housed within a semiconductor package. The controller is configured to: determine whether first image data generated by the image sensor contain features of an object; based on whether the first image data contain the features of the object, generate programming signals for the image sensor; and control, based on the programming signals, the image sensor to generate second image data.