Super-Resolution Image Generation via Diagonal Pixel Shift
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Solution Overview
Problem
Existing super-resolution image generation techniques for line scan cameras are costly and computationally intensive, requiring high precision optics and multiple low-resolution images, which limits their effectiveness and efficiency.
Innovation Solution
A method that generates a super-resolution image from a pair of diagonally pixel-shifted low-resolution images, adaptively enhances them, and combines them using bilinear stacking, preserving edge data for contrast enhancement, thereby achieving higher resolution without the need for motion estimation or complex interpolation methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high precision optics and image sensor are used to increase spatial resolution, then image quality is improved, but cost increases prohibitively
Solution Approach 1:
The patent creates multiple low-resolution images with subpixel shifts and combines them to generate a super-resolution image, effectively copying information from multiple perspectives to achieve high resolution without requiring expensive high-precision optics
Solution Approach 2:
The patent introduces the temporal dimension by capturing multiple images at different subpixel positions and combines them through computational processing, transforming a spatial resolution problem into a temporal-spatial solution that avoids costly hardware upgrades
2Measurement precision
If sensor pixel size is reduced to increase number of pixels per unit area, then spatial resolution is improved, but light capture decreases leading to increased noise
Solution Approach 1:
The patent merges multiple low-resolution images captured at different subpixel positions to generate a single super-resolution image, combining the signal information from multiple captures to maintain signal-to-noise ratio while achieving higher spatial resolution
3Measurement precision
If chip size is increased to maintain same signal to noise ratio while increasing spatial resolution, then spatial resolution is improved, but capacitance increases causing difficulties in charge transfer
Solution Approach 1:
The patent uses computational copying of image information from multiple subpixel-shifted captures to achieve high resolution, avoiding the need to physically increase chip size and the associated capacitance problems
4Measurement precision
If three or more low-resolution images are used for super-resolution enhancement, then image quality is improved, but processing complexity and time increase
Solution Approach 1:
The patent achieves effective super-resolution using exactly two low-resolution images with diagonal subpixel shifts, applying partial action by using the minimum necessary number of images to accomplish the enhancement without the excessive processing requirements of three or more images
5Measurement precision
If existing super-resolution algorithms are implemented, then spatial resolution is improved, but processing speed decreases due to considerable processing power requirements
Solution Approach 1:
The patent extracts and preserves edge data from the low-resolution images before combining them, separating the critical structural information from the full image data to reduce processing complexity and improve processing speed while maintaining spatial resolution enhancement
Data Source
AI summary
A method for generating a super-resolution image and related device is provided. In one aspect, the method comprises: receiving a first low-resolution image and a second low-resolution image, the first low-resolution image and second low-resolution image have a first spatial resolution and having been captured simultaneously by a pair of pixel arrays of a common image sensor, wherein the pixel arrays of the image sensor are located as to be diagonally shifted from each other by a sub-pixel increment; adaptively enhancing the first low-resolution and the second low-resolution images to generate an enhanced first low-resolution image and an enhanced second low-resolution image, respectively; mapping (e.g., non-uniformly) pixels of each of the enhanced first and second low-resolution images to a super-resolution grid having a spatial resolution greater than the first spatial resolution to generate a first intermediate super-resolution image and a second intermediate super-resolution image, respectively; and combining the first intermediate super-resolution image and second intermediate super-resolution image to generate a composite super-resolution image.