Zoom Digital Camera With Adaptive FOV and Selective Resolution
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Solution Overview
Problem
Existing digital cameras in mobile devices face challenges in efficiently zooming into specific field-of-view (FOV) segments while maintaining high spatial resolution, particularly with the use of binning sensors that reduce pixel resolution.
Innovation Solution
A mobile device with a binning sensor configured to operate in full resolution mode for certain segments and binning resolution mode for others, allowing selective capture and processing of regions of interest (ROIs) in higher pixel resolution, while maintaining efficient data handling and frame rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a multi-camera system uses a wide FOV camera to capture a particular FOV segment, then the spatial resolution is reduced, but the entire FOV segment can be included; if a telephoto camera is used, then the spatial resolution is improved, but the FOV segment may not be fully included
Solution Approach 1:
The patent implements dynamic FOV adjustment by enabling the wide FOV camera to capture images at multiple zoom levels (0.5x, 1x, 1.5x, 2x) through software-controlled cropping and processing of different sensor segments. This allows the system to adaptively select the appropriate FOV and resolution combination based on the desired capture scenario, resolving the contradiction between FOV coverage and spatial resolution.
2Reliability
If pixel binning is applied to increase light sensitivity and reduce noise, then the spatial resolution is reduced, but image quality in low light is improved
Solution Approach 1:
The patent applies different processing strategies to different segments of the image sensor. For regions requiring high spatial resolution, the system processes individual pixel data without binning. For regions where light sensitivity is prioritized, binning is applied. This local differentiation allows the system to optimize image quality for specific regions of interest while maintaining overall system efficiency.
Solution Approach 2:
The system dynamically switches between binning and non-binning modes based on the capture scenario and region of interest. The processor can selectively apply binning to certain sensor segments while maintaining full resolution in other segments, allowing adaptive optimization between image quality and spatial resolution.
3Measurement precision
If the entire image sensor operates in full resolution mode, then the spatial resolution is maximized, but the bandwidth and power consumption increase
Solution Approach 1:
The patent divides the image sensor into multiple independent segments that can be processed separately. Instead of processing the entire sensor at full resolution, the system identifies regions of interest and processes only those segments at full resolution, while other segments can be processed at lower resolution or discarded. This segmentation significantly reduces bandwidth and power consumption while maintaining high resolution where needed.
Solution Approach 2:
The system applies full resolution processing only to the necessary portions of the image (regions of interest) rather than processing the entire sensor output at full resolution. This partial action approach maintains high spatial resolution for important areas while reducing overall computational load, bandwidth requirements, and power consumption.
4Productivity
If multiple sensor segments are processed independently, then the processing speed is improved, but the coordination and synchronization complexity increases
Solution Approach 1:
The patent implements segmentation of the sensor into independent processing segments that can be handled by different processing pipelines simultaneously. Each segment can be processed independently through parallel operations, improving overall processing throughput. The system manages coordination through structured data flow and synchronized processing stages, balancing parallelism with system complexity.
Data Source
AI summary
Mobile devices comprising a first camera having a first camera field-of-view (FOV1) and including a first image sensor configured to operate a first segment of the first image sensor in a full resolution-mode for capturing full resolution image data and to operate a second segment of the first image sensor in a binning resolution mode for capturing binning resolution image data and a processor for analyzing image data of the first camera to select a region of interest (ROI) in a scene and for configuring the first image sensor so that the selected ROI is captured in full resolution. In some examples, a mobile device further comprises a second camera having a second FOV (FOV2) and including a second image sensor configured to capture FOV2, wherein the analysis of image data to select a ROI is performed by analysing image data of the second camera.