Per-Channel Image Intensity Correction Using Triangulation
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Solution Overview
Problem
Conventional imaging systems face challenges in correcting distortion introduced by lenses and image sensor arrays, particularly due to uneven light attenuation and chromatic aberration, which are costly and numerically unstable to address using high-order two-dimensional polynomial interpolation.
Innovation Solution
The implementation of bi-cubic interpolation using Bezier surfaces for per-channel image intensity correction, which is numerically stable and easier to implement, both in hardware and software, to generate corrected spectral data by applying bi-cubic patches across the image plane.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-order two-dimensional polynomial interpolation is used to correct image intensity distortion, then correction accuracy is improved, but computational cost and numerical instability increase
Solution Approach 1:
The patent divides the image plane into multiple triangular regions using a triangulation scheme. Instead of applying a single complex high-order polynomial across the entire image, the correction is performed separately on each triangle using simple linear interpolation. This segmentation reduces computational complexity while maintaining correction accuracy, as each local region can be corrected independently with lower-order mathematics.
Solution Approach 2:
The patent transforms the problem from applying a two-dimensional high-order polynomial across the image plane to using a one-dimensional linear interpolation along the edges of triangular regions. By changing the dimensional approach of the interpolation (from global 2D to local 1D along triangle edges), the method achieves correction with reduced computational burden and improved numerical stability.
2Reliability
If multiple lens combinations are used to correct distortion in hardware, then distortion correction effectiveness is improved, but device cost and complexity increase
Solution Approach 1:
The patent replaces the mechanical/optical approach of using multiple lens combinations with a digital signal processing approach. Instead of adding physical lens elements to correct distortion optically, the invention uses computational methods (triangulation-based linear interpolation) to correct the captured image digitally. This substitution eliminates the need for complex hardware while achieving the same correction goal.
Solution Approach 2:
The patent performs distortion correction as a preliminary processing step in the digital imaging pipeline, immediately after image capture and before final image output. By addressing the distortion problem in the digital domain early in the processing flow, the system avoids the need for complex optical correction mechanisms, as the correction is applied computationally rather than optically.
Data Source
AI summary
Techniques for per-channel image intensity correction includes linear interpolation of each channel of spectral data to generate corrected spectral data.