Dual-Sensor ROI Imaging for High-Resolution Subject Capture
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Solution Overview
Problem
The demand for higher resolution imaging systems is increasing, but scaling pixel numbers in imaging sensors leads to diminishing returns and unnecessary processing load, as many applications only require high resolution in specific regions of interest, such as a person's face, rather than the entire field of view.
Innovation Solution
An imaging system comprising a color and a grayscale sensor, where the grayscale sensor captures images with higher resolution within the color sensor's field of view, and a processor generates an output image by determining regions of interest and applying spatial filters to achieve high resolution only in relevant areas, using both color and grayscale image data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the number of pixels in imaging sensors is increased to achieve higher resolution, then imaging resolution is improved, but device size and processing load increase
Solution Approach 1:
The patent applies local quality by capturing high-resolution grayscale images only in the region of interest (ROI) while maintaining lower resolution in other areas. The grayscale sensor captures high-resolution data specifically where needed (e.g., face area), and the processor selectively processes only this region to enhance color image quality, avoiding the need to process entire high-resolution images and thus reducing overall processing load.
Solution Approach 2:
The patent segments the image processing task by dividing the field of view into regions of interest and non-interest areas. The grayscale sensor captures high-resolution data only for the ROI, and the processor separately handles ROI enhancement and background processing, thereby reducing the total processing burden compared to processing entire high-resolution images.
2Measurement precision
If the number of pixels in imaging sensors is increased to achieve higher resolution, then imaging resolution is improved, but manufacturing cost increases
Solution Approach 1:
The patent uses local quality by deploying a grayscale sensor with high pixel density only where needed (in the ROI area) rather than across the entire sensor array. This allows the system to achieve high resolution in critical areas using fewer total pixels, thereby reducing manufacturing costs compared to using a full high-resolution color sensor.
Solution Approach 2:
The grayscale image acts as an intermediary that provides high-resolution structural information for the ROI. This intermediary data is used to guide the processing of the color image, allowing the system to achieve high-resolution color output in the ROI without requiring a full high-resolution color sensor, thus reducing manufacturing costs.
3Measurement precision
If high resolution is applied over the entire field of view, then imaging resolution is improved, but processing load increases unnecessarily
Solution Approach 1:
The patent applies local quality by enhancing resolution only in the region of interest rather than across the entire field of view. The processor identifies the ROI (e.g., face area) and applies computationally intensive high-resolution processing only to this region, while leaving other areas at lower resolution, thereby significantly improving processing efficiency.
Solution Approach 2:
The patent uses partial action by applying high-resolution processing only to the necessary portion of the image (the ROI) rather than the entire image. This partial processing approach achieves the required quality for the subject area while avoiding the excessive processing load that would result from processing the complete high-resolution image.
Data Source
AI summary
An imaging system includes a color imaging sensor that acquires a color image having a color image resolution and color image field of view, a grayscale imaging sensor that acquires a grayscale image having a grayscale image resolution and grayscale image field of view, wherein the grayscale image field of view is at least partially within the color image field of view, and the grayscale image resolution is greater than the color image resolution with respect to the color image field of view, and a first processor that generates an output image by obtaining the color image and the grayscale image, determining a color image region of interest (ROI), bounded by a color image ROI boundary box within the color image, such that the color image ROI includes the subject, and determining a grayscale image ROI, bounded by a grayscale image ROI boundary box within the grayscale image.