Image Fusion With Color-Depth Adjustment for Capsule Endoscopy
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Solution Overview
Problem
Medical capsules like capsule endoscopes cannot capture clear images of the same body part under different colored lights, leading to blurred images that require lengthy fusion processes, hindering immediate and accurate medical diagnosis.
Innovation Solution
An image fusion device with components for image feature analysis, color identification, maximum depth comparison, and pixel depth analysis to adjust color depths, generating a clear fusion image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If images are captured under different colored lights and fused using traditional methods, then clear images can be obtained, but the processing time is too long for immediate diagnosis
Solution Approach 1:
The image processing is segmented into distinct components: feature analysis, color identification, depth comparison, and fusion processing. Each component handles specific tasks independently, allowing parallel processing of multiple images captured under different colored lights, thereby reducing overall processing time while maintaining image clarity
Solution Approach 2:
The system performs preliminary analysis of image features, color characteristics, and depth information before the actual fusion process. By pre-processing and organizing the captured images with metadata about lighting conditions and depth, the fusion algorithm can operate more efficiently on structured data, reducing the time required for immediate diagnosis
2Loss of information
If medical capsules capture images under different colored lights, then more information about body parts can be obtained, but the capsule hardware is not capable of capturing under multiple colors
Solution Approach 1:
Instead of equipping the capsule with multiple light sources or sensors, the system uses a single light source to capture images and then creates virtual copies of the imaging process by processing the same image data through different color channel analyses and depth estimations. This software-based approach replicates the effect of multiple light sources without adding hardware complexity
Solution Approach 2:
The system captures images under different lighting conditions and then applies parameter changes during processing by adjusting color depth values, brightness, and contrast for different color channels. This allows the extraction of information that would normally require multiple physical light sources, but achieves through digital parameter manipulation instead of hardware changes
Data Source
AI summary
An image fusion device and an image fusion parallel optimization method are provided. After a plurality of images are aligned to each other to form a superimposed image, the image fusion device filters the superimposed image to obtain a feature image. The image fusion device compares color depths of pixel points in each of a plurality of pixel regions of the feature image with each other to determine a maximum color depth of each of the plurality of pixel regions. When a relationship between the color depth of any one of the pixel points and the maximum color depth in each of the plurality of pixel regions does not meet a preset relationship, the image fusion device adjusts the color depth of the one of the pixel points according to the maximum color depth. The image fusion device generates a fused image according to the adjusted feature image.