Ambient Light Image Correction Using Motion Error Subsets
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Solution Overview
Problem
Images captured by a camera under mixed illumination conditions, including ambient and controlled light, suffer from errors due to object movement between frames, which complicates accurate color comparison and correction.
Innovation Solution
A method involving capturing multiple primary images with varying illumination intensity, estimating motion-induced error using displacement vectors between grid elements, and performing ambient light correction on sub-sets with minimal error, generating an ambient light corrected image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If ambient light correction is performed by comparing pixels of captured images, then ambient light can be corrected to enable accurate color determination, but errors are introduced when there is any movement of the object between frames
Solution Approach 1:
The patent divides the image into multiple blocks and calculates displacement vectors for each block separately. This segmentation allows the system to handle different motion characteristics in different regions of the image, improving overall accuracy while maintaining computational efficiency.
Solution Approach 2:
The patent performs displacement estimation and error value calculation before performing ambient light correction. By preliminarily identifying and compensating for motion effects through displacement vectors, the system prevents motion-induced errors from affecting the final color determination accuracy.
2Measurement precision
If multiple primary images are captured with controlled intensity of illumination varying over time, then ambient light correction can be improved, but the complexity of the image processing system increases
Solution Approach 1:
The patent segments the image into blocks and processes displacement vectors for each block independently. This segmentation reduces the overall computational complexity by breaking down the large-scale image processing into smaller, manageable units that can be processed in parallel.
Solution Approach 2:
The patent extracts only the necessary displacement information from each image block rather than processing all pixel data. By taking out only the relevant motion parameters (displacement vectors), the system achieves accurate ambient light correction while minimizing computational complexity.
3Measurement precision
If displacement vector matrix is calculated by dividing images into grid elements and matching corresponding elements, then motion error can be accurately estimated, but the processing time and computational load increase
Solution Approach 1:
The patent divides the image into grid blocks and processes displacement estimation for each block separately. This segmentation enables parallel processing of different image regions, reducing overall processing time while maintaining accurate motion error estimation through localized displacement vector calculation.
Solution Approach 2:
The patent calculates displacement vectors for representative grid blocks rather than every single pixel. This partial action approach provides sufficient motion error estimation accuracy for ambient light correction while significantly reducing the computational load and processing time compared to full-pixel analysis.
Data Source
AI summary
According to an aspect, there is provided a method for minimising error in ambient light corrected image due to motion, the method comprising: capturing a plurality of primary images with controlled intensity of illumination varying over time, estimating an error value due to motion for each of a plurality of sub-sets of the plurality of primary images, and performing ambient light correction on an error minimised sub-set of primary images having the lowest estimated error value to generate an ambient light corrected (ALC) image with a minimised error. Estimating the error value for each sub-set of the plurality of primary images comprises identifying a pair of primary images in the sub-set including a first primary image and a second primary image, wherein the first primary image is captured temporally before the second primary image, determining a displacement vector matrix between the pair of primary images, and estimating the error value for the sub-set of primary images based on the displacement vector matrix between the pair of primary images. Determining the displacement vector matrix includes dividing the first primary image into a plurality of first grid elements and dividing the second primary image into a plurality of second grid elements, matching first grid elements to second grid elements which correspond to the same position on the object, and determining a displacement vector between each matched first grid element and second grid element to determine a displacement vector matrix describing the displacement vector of each grid element.