Endoscope Motion Detection via Mode-Adaptive Weighting
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Solution Overview
Problem
Endoscope devices face challenges in accurately detecting motion between images captured using white light imaging and narrow band imaging due to differences in luminance components and filter arrangements, which affect the accuracy of motion detection processing.
Innovation Solution
An image processing apparatus that performs averaging processing on pixel values of pixels with different color filters to generate motion detection images, with adjusted weights for luminance components in both white light and narrow band imaging modes, enabling accurate motion detection between images captured at different times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If motion detection is performed using conventional averaging processing on all pixel values in Bayer array, then processing is simplified, but motion detection accuracy deteriorates due to unequal contribution of color components to luminance signal
Solution Approach 1:
The patent applies different weighting coefficients to different color components (R, G, B) when generating the luminance signal for motion detection. Specifically, it sets weight Wr for red component, Wg for green component, and Wb for blue component, where these weights are adjusted based on imaging mode (WLI or NBI) to ensure that the color component contributing most to luminance in each mode has the greatest weight. This local differentiation in weighting resolves the contradiction by maintaining processing simplicity while improving motion detection accuracy through mode-appropriate weighting.
Solution Approach 2:
The patent dynamically changes the weighting parameters (Wr, Wg, Wb) based on the imaging mode. In WLI mode, it uses weights optimized for white light conditions, while in NBI mode, it uses weights optimized for narrow band conditions. This parameter adaptation allows the system to maintain high motion detection accuracy across different imaging modes without increasing processing complexity, as the weighting scheme remains consistent within each mode.
2Device complexity
If white light imaging and narrow band imaging use the same motion detection processing, then processing is unified, but detection accuracy deteriorates due to different luminance component characteristics in each imaging mode
Solution Approach 1:
The patent implements a dynamic weighting system that automatically adapts to different imaging modes. The image processing apparatus switches between different sets of weighting coefficients (Wr, Wg, Wb) depending on whether WLI or NBI is being performed. This dynamic adaptation ensures that motion detection accuracy is optimized for each imaging mode's specific luminance characteristics, while maintaining a unified processing framework that selects appropriate parameters based on the current mode.
Solution Approach 2:
The patent changes the parameters (weighting coefficients) based on the imaging mode being used. For WLI, it uses weights that reflect the luminance contribution of each color component under white light illumination. For NBI, it uses different weights that reflect the luminance characteristics under narrow band illumination. This parameter change approach allows the system to maintain processing unity through a single motion detection algorithm while achieving mode-specific optimization for accurate motion detection.
3Device complexity
If conventional motion detection is used in narrow band imaging, then processing is straightforward, but accuracy deteriorates due to unbalanced color component ratios in NBI
Solution Approach 1:
The patent recognizes that narrow band imaging has different luminance characteristics compared to white light imaging, particularly in the distribution of color components. It applies locally optimized weighting coefficients (Wr, Wg, Wb) specifically for NBI mode that account for the unbalanced color component ratios inherent in narrow band illumination. This local optimization improves motion detection accuracy in NBI without complicating the overall processing, as the same weighted averaging approach is used, just with mode-specific parameters.
Data Source
AI summary
An image processing apparatus configured to perform averaging processing on pixel values of pixels having different color filters to obtain a signal value, and generate motion detection images based on the signal value in such a way that, in WLI, a weight of a pixel value for a filter for passing light of a luminance component of a captured image in WLI is set to be larger than or equal to a weight of a pixel value for a different filter while in NBI, a weight of a pixel value for a filter for passing light of a luminance component of a captured image in NBI is set to be larger than or equal to a weight of a pixel value for a different filter. Based on the captured images at different points in time, the image processing apparatus detects motion between two of the generated motion detection images.