Spectral Image Processing for Real-Time Color Vision Compensation
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Solution Overview
Problem
Existing image-recoloring techniques for color vision deficiencies are not adaptable to multiple types and severities of CVDs, are too slow for real-time application, and introduce temporal instability, making them unusable for videos or real-time graphics.
Innovation Solution
A daltonization system that generates transformation curves based on color deficiency profiles to adjust images quickly and seamlessly, using spectral representations and matrix operations to redistribute wavelengths, preserving grayscale and luminance, and applying these curves in real-time or near-real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If existing daltonization algorithms are used to improve color differentiation for CVDs, then color information becomes more distinguishable, but the processing time becomes too long for real-time applications
Solution Approach 1:
The patent pre-calculates and stores transformation curves for different types and severities of color vision deficiencies before runtime. During real-time video processing, the system simply applies these pre-computed curves through matrix operations rather than calculating daltonization parameters from scratch, reducing processing time from minutes to milliseconds per frame.
Solution Approach 2:
The patent transforms the daltonization problem from complex iterative optimization to direct matrix multiplication by changing the parameter representation to spectral power distributions and using pre-computed transformation matrices. This parameter transformation enables real-time processing while maintaining color differentiation quality.
2Loss of information
If existing daltonization techniques are applied to images, then color differentiation is improved for specific CVD types, but the techniques cannot be adapted to multiple types and severities of CVDs
Solution Approach 1:
The patent creates a universal daltonization system that generates separate transformation curves for each CVD type (protanopia, deuteranopia, tritanopia) and severity level. The system automatically selects and applies the appropriate curve based on the user's diagnosed CVD profile, making a single system adaptable to all major types and severities of color vision deficiencies.
Solution Approach 2:
The patent applies different transformation curves tailored to specific CVD types and severities rather than using a single generic transformation. Each CVD category receives optimized color redistribution parameters matched to its specific physiological characteristics, providing locally optimized color differentiation for each user profile.
3Loss of information
If existing daltonization methods are used for video processing, then color information is redistributed, but temporal instability occurs making the experience jarring
Solution Approach 1:
The transformation curves are pre-computed to ensure consistency across all video frames. By establishing the color transformation parameters before video playback and applying them uniformly to every frame, the system eliminates temporal fluctuations and instability that would otherwise occur with frame-by-frame recalculation.
Data Source
AI summary
The technology disclosed herein involves using a transformation curve to modify colors of images so that those images are more easily viewed by persons with a color vision deficiency (CVD). The transformation curve is applied to spectral versions of images in which each pixel has a spectral representation to modify the spectral versions of the images. A spectral version of an image is modified by, for each pixel of the spectral version of the image, modifying intensities of one or more wavelengths by applying the one or more wavelengths to the transformation curve, which transforms the intensities from source wavelengths to destination wavelengths. The modified spectral version of the image is then modified to a modified version of the image in a color space, such as the RGB color space.