Edge Detection System Using Partially-Filled Reference Images
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Solution Overview
Problem
Existing edge detection methods in image sensors are inefficient due to the need for interpolation of color pixel data to generate panchromatic images, which slows down the edge map generation process and reduces image resolution.
Innovation Solution
The method involves skipping color and/or panchromatic pixels to produce a partially-filled reference panchromatic image and truncating panchromatic pixel values based on illumination levels, allowing for faster edge detection by reducing data processing requirements without significantly compromising image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If color pixel data is interpolated to generate complete panchromatic images, then image resolution is maintained, but edge detection speed decreases and computational load increases
Solution Approach 1:
The patent applies partial action by generating panchromatic images only at locations where edge pixels are detected, rather than processing the entire image. The system first performs a quick edge detection pass, then selectively generates high-resolution panchromatic images only in regions containing edges, significantly reducing computational load while maintaining edge detection quality
Solution Approach 2:
The image processing is segmented into multiple stages: initial edge detection using lower-resolution data, identification of edge-containing regions, and selective generation of high-resolution panchromatic images only for those regions. This segmentation allows the system to avoid unnecessary computation in non-edge areas
2Measurement precision
If complete panchromatic images are generated for all pixels, then image quality is maximized, but data processing time and computational resources increase
Solution Approach 1:
The patent implements local quality by applying different processing levels to different regions of the image. High-quality panchromatic image generation is applied only to local regions containing edges, while non-edge regions use lower processing requirements. This allows the system to optimize overall processing time while maintaining high quality where it matters most
Solution Approach 2:
Instead of generating complete panchromatic images for all pixels, the system performs partial action by generating high-resolution panchromatic data only for pixels located in edge regions. This selective approach significantly reduces data processing time and computational resource requirements
Data Source
AI summary
An edge detection method includes reading at least a portion of wide-band pixel signals generated by wide-band pixels of an image sensor. The image sensor also includes narrow-band pixels that generate narrow-band pixel signals that remain unread. The method also includes sending the wide-band pixel signals to an image signal processor, forming a partially-filled reference image based on data from the wide-band pixel signals; and applying an edge-forming technique to the partially-filled reference image to produce an edge map. An edge detection system includes a two-dimensional array of pixels having wide-band pixels and narrow-band pixels, an image signal processor for producing an edge map from a partially-filled reference image, and a readout circuit for generating the partially-filled reference image for the image signal processor. The partially-filled reference is based only on at least part of the wide-band pixels.