Endoscopic Gamma Correction via YCbCr Gain
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Solution Overview
Problem
Endoscopic imaging devices face challenges with intensity gradients and shadows due to varying distances and light blockages, requiring localized adjustments to improve image visibility.
Innovation Solution
A medical system with a controller that converts RGB pixel data to YCbCr format, calculates a magnitude-based gain for each pixel, and applies different gains to luminance and chroma values using look-up tables to adjust pixel data, enhancing image visibility without altering light output.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If light output from the light source is increased to improve visibility, then brighter areas become overexposed (hotspots), but if light output is decreased to reduce hotspots, then darker areas become underexposed (shadows)
Solution Approach 1:
The patent applies different gain values to different regions of the image based on local intensity characteristics. The controller divides the image into multiple regions and applies localized gain adjustments, allowing bright areas to be toned down while dark areas are brightened, thereby resolving the contradiction between avoiding hotspots and preventing shadows.
Solution Approach 2:
The system dynamically changes the gain parameter for different pixel regions based on their intensity values. By calculating local statistics (mean and standard deviation) for each region and adjusting gain accordingly, the system adapts the illumination parameters locally to eliminate both hotspots and shadows simultaneously.
2Illumination intensity
If global light control is used to adjust overall image brightness, then the entire image brightness changes uniformly, but this cannot address localized visibility issues in different regions
Solution Approach 1:
The patent transitions from global light control to local quality control by dividing the image into multiple regions and applying region-specific gain adjustments. Each region's brightness is adjusted independently based on its local characteristics, enabling the system to address localized visibility issues while maintaining overall image quality.
Solution Approach 2:
The image is segmented into multiple regions, and each region is processed independently with its own gain calculation. This segmentation allows the system to apply different brightness adjustments to different parts of the image, providing the adaptability needed to handle localized visibility problems that global control cannot address.
3Object-affected harmful factors
If image processing is performed to adjust localized regions, then visibility is improved, but processing complexity and computational requirements increase
Solution Approach 1:
The patent applies partial action by processing only the necessary regions with the complexity required for their specific needs. Rather than applying complex processing uniformly across the entire image, the system calculates local statistics and applies gain adjustments only where needed, reducing overall computational complexity while maintaining visibility improvement.
Data Source
AI summary
A medical system includes a shaft having a proximal end and a distal end, an imaging device at the distal end of the shaft, and a controller, the controller receives image data comprising pixel data from the imaging device, the pixel data including a plurality of individual pixel values, converts the pixel data from a RGB format to a YCbCr format, and forms adjusted pixel data by applying a gain to the pixel data, wherein the gain is based on a Y value, a Cb value, and a Cr value of the individual pixel values of the converted pixel data.