Hyperspectral Image Sensor Illumination Correction
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Solution Overview
Problem
Existing image acquisition methods fail to accurately measure or estimate the spatial distribution of illumination, leading to color inconstancy and inconsistency in images, especially under multiple illumination conditions, making it difficult to distinguish objects from backgrounds effectively.
Innovation Solution
An image acquisition apparatus and method utilizing hyperspectral imaging technology, including a hyperspectral image sensor and a processor that extracts and normalizes the spectrum of each pixel, analyzes the spatial distribution of illumination, and corrects colors using an average illumination spectrum, allowing for effective object-background separation and color correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single illumination measurement or estimation method is used, then the processing complexity is reduced, but the spatial distribution of illumination cannot be accurately measured or estimated
Solution Approach 1:
The patent divides the image into multiple regions (foreground objects and background) and processes each region separately to estimate illumination characteristics. By segmenting the image and analyzing different spatial regions independently, the system accurately captures the spatial distribution of illumination without requiring a completely complex system redesign.
Solution Approach 2:
The patent transitions from measuring a single average illumination value to measuring illumination across multiple spatial dimensions. By analyzing illumination at different locations and depths within the image, the system captures the three-dimensional spatial distribution of illumination, transforming a one-dimensional measurement problem into a multi-dimensional solution.
2Measurement precision
If chromatic adaptation correction is applied to correct color inconsistency, then color accuracy is improved, but the ability to distinguish objects from background under multiple illuminations deteriorates
Solution Approach 1:
The patent applies different color correction strategies to different regions of the image. Instead of applying a uniform correction to the entire image, it analyzes and corrects colors locally in foreground object regions versus background regions separately. This allows accurate color correction for objects while preserving the ability to distinguish them from the background, as each region receives correction appropriate to its illumination characteristics.
Solution Approach 2:
The patent introduces an intermediary illumination spectrum estimation as a mediator between the raw image data and the final color correction. By estimating the illumination spectrum as an intermediate step and using it to normalize both object and background regions, the system achieves accurate color representation while maintaining distinguishability through the preservation of spectral signatures.
3Measurement precision
If spectrum normalization is performed for each pixel, then color consistency is improved, but the processing time and computational load increase
Solution Approach 1:
The patent merges the illumination correction operation with the existing image processing pipeline. Instead of performing spectrum normalization as a separate, time-consuming step for each pixel, it integrates the correction into the overall image processing flow, combining multiple operations into unified processing stages that reduce total computational time while maintaining color consistency.
Solution Approach 2:
The patent applies spectrum normalization selectively to key regions and critical wavelength ranges rather than uniformly to every pixel across the entire spectrum. By applying partial correction to the most important spectral bands and regions, the system achieves sufficient color consistency with reduced computational overhead, avoiding excessive processing time.
Data Source
AI summary
Provided is an image acquisition apparatus including a first hyperspectral image sensor configured to obtain a first image, and a processor configured to process the first image obtained by the first hyperspectral image sensor, wherein the processor is further configured to extract a spectrum of each pixel of the first image obtained by the first hyperspectral image sensor, correct the spectrum by normalizing the spectrum of each pixel, distinguish an object from a background within the first image by recognizing a pattern of the spectrum of each pixel, and correct a color of the object and a color of the background by using a spatial distribution of illuminations.


