Endoscope Image Processing Balancing Resolution and Noise
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Solution Overview
Problem
Endoscope systems face increased processing costs and inefficiencies due to the need for real-time image processing, particularly with high-resolution images, as existing methods do not adequately account for differences in illumination light and lens aperture, leading to wasted processing resources and suboptimal image quality.
Innovation Solution
An endoscope system that includes an objective lens, an image capturing unit, low-frequency and high-frequency component extractors, and an image quality enhancement processor, which adjusts processing based on condition information such as light type and aperture settings to balance processing load and image quality, applying noise reduction, color correction, and frequency band emphasis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If all image processing is performed in the size as it is of the input image, then image quality improvement can be achieved, but processing cost (processing time, hardware scale) increases
Solution Approach 1:
The patent segments the image processing into frequency-based components (low-frequency and high-frequency components). The low-frequency component extraction unit extracts low-frequency components from the input image, and the high-frequency component extraction unit extracts high-frequency components. This segmentation allows different processing strategies to be applied to different frequency components, reducing overall processing load while maintaining image quality.
Solution Approach 2:
The patent applies different processing quality levels to different frequency components based on their characteristics. Low-frequency components undergo more intensive image quality enhancement processing, while high-frequency components are processed with less intensive operations. This local quality approach optimizes the balance between processing load and image quality improvement.
2Manufacturing precision
If image processing is performed at full resolution, then image quality is improved, but processing time increases
Solution Approach 1:
The patent divides the image processing into frequency-based segments, allowing low-frequency and high-frequency components to be processed separately. This segmentation enables the system to apply computationally intensive quality enhancement primarily to low-frequency components while using simpler processing for high-frequency components, thereby reducing total processing time while maintaining overall image quality.
Solution Approach 2:
The patent applies partial action by selectively applying intensive image quality enhancement processing only to low-frequency components rather than processing the entire image at full resolution. This partial processing approach significantly reduces computation time while still achieving acceptable image quality improvement.
3Device complexity
If the same image processing is applied to all illumination types, then processing simplicity is maintained, but processing efficiency decreases due to wasted resources
Solution Approach 1:
The patent introduces dynamic adaptation by detecting the illumination type (white light or special light) and automatically adjusting the image processing strategy accordingly. When special light imaging is detected, the system extracts and processes only low-frequency components with intensive enhancement, whereas white light imaging receives different processing treatment. This dynamic adjustment optimizes processing efficiency for each illumination type without increasing system complexity.
Solution Approach 2:
The patent changes processing parameters based on illumination type detection. The image processing is adapted by modifying which frequency components are extracted and enhanced based on whether the input is from white light or special light sources. This parameter change approach improves processing efficiency by avoiding unnecessary processing operations for each illumination type.
Data Source
AI summary
The present technology relates to an endoscope system in which resolution and an S/N ratio are adjusted to be well-balanced depending on an imaging condition, and further capable of changing a processing load depending on the imaging condition, a method for operating the endoscope system, and a program.From an image signal in a body cavity imaged by an endoscope apparatus, a low frequency image including a low frequency component and a high frequency image including a high frequency component are extracted. The low frequency image is reduced by a predetermined reduction ratio, and, after image quality improvement processing is performed, is enlarged by an enlargement ratio corresponding to the reduction ratio. At that time, based on condition information indicating an imaging state, when brightness at the time of imaging is sufficient and the high frequency component does not include noise components a lot, the low frequency image and the high frequency image are added to be output as an output image. In addition, based on the condition information, when the brightness at the time of imaging is not sufficient and the high frequency component includes the noise components a lot, only the low frequency image is output as the output image. The present technology can be applied to the endoscope system.