Image Sensor Control Method for Resolution and Noise Trade-off
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Solution Overview
Problem
Current image sensors face challenges in enhancing image resolution while maintaining a high signal-to-noise ratio, as merging photosensitive pixels reduce resolution and converting color block images into imitating images through interpolation is resource-intensive and time-consuming, leading to poor user experience.
Innovation Solution
A control method that outputs merged and color block images, converts specific regions of the color block image into imitating images using a first interpolating method, and other regions of the merged image using a second interpolating method with lower complexity, synthesizing these to enhance image resolution and reduce processing time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If photosensitive pixels are merged to increase signal-to-noise ratio, then signal-to-noise ratio is improved, but resolution is decreased
Solution Approach 1:
The image is divided into multiple regions with different processing priorities. The first region (main region of interest) undergoes full interpolation processing to maintain high resolution, while the second region (peripheral region) uses simplified processing or merging to maintain signal-to-noise ratio. This segmentation allows simultaneous optimization of both resolution and signal quality in different areas.
Solution Approach 2:
Different processing qualities are applied to different regions of the image. The main region of interest receives high-quality interpolation processing to preserve resolution, while peripheral regions accept lower-quality merged processing. This local quality differentiation resolves the contradiction by allowing resolution to be maintained where most needed while accepting merging benefits in less critical areas.
2Manufacturing precision
If color block image is converted to imitating image through interpolation to enhance resolution, then resolution is improved, but processing time and resource consumption increase
Solution Approach 1:
The image processing is segmented into different regions with different interpolation requirements. The first region (main region of interest) undergoes complete interpolation processing to achieve high resolution, while the second region (peripheral region) uses simplified processing or direct merging. This segmentation reduces overall processing time and resource consumption while maintaining high resolution where most needed.
Solution Approach 2:
Instead of applying full interpolation processing to the entire image, the patent applies interpolation only partially to the main region of interest. This partial action approach achieves sufficient resolution enhancement for the most important areas while significantly reducing processing time and computational resources compared to processing the entire image at full resolution.
Data Source
AI summary
A control method for controlling an electronic apparatus includes controlling an image sensor to output a merged image and a color block image of a same scene; defining a first predetermined region using the merged image based on a user input; converting the color block image into a first imitating image and converting the merged image into a restored image, wherein a second predetermined region in the color block image is converted using a first interpolating method, and the second predetermined region corresponds to the first predetermined region, and wherein a third predetermined region in the merged image is converted using a second interpolating method, and the third predetermined region corresponds to a first region outside the first predetermined region; obtaining a second imitating image by synthesizing the first imitating image and the restored image. An electronic apparatus is also provided.