Influence of edge enhancement applied in endoscopic systems on sharpness and noise

Journal Article (2022)
Authors

G. Geleijnse (Erasmus MC)

B. Rieger (ImPhys/Computational Imaging)

Research Group
ImPhys/Computational Imaging
Copyright
© 2022 Geert Geleijnse, B. Rieger
To reference this document use:
https://doi.org/10.1117/1.JBO.27.10.106001
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Publication Year
2022
Language
English
Copyright
© 2022 Geert Geleijnse, B. Rieger
Related content
Research Group
ImPhys/Computational Imaging
Issue number
10
Volume number
27
DOI:
https://doi.org/10.1117/1.JBO.27.10.106001
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Abstract

SignificanceFlexible endoscopes are essential for medical internal examinations. Digital endoscopes are connected to a video processor that can apply various operations to enhance the image. One of those operations is edge enhancement, which has a major impact on the perceived image quality by medical professionals. However, the specific methods and parameters of this operation are undisclosed and the arbitrary units to express the level of edge enhancement differ per video processor.AimObjectively quantify the level of edge enhancement from the recorded images alone, and measure the effect on sharpness and noise.ApproachEdge enhancement was studied in four types of flexible digital ear nose and throat endoscopes. Measurements were performed using slanted edges and gray patches. The level of edge enhancement was determined by subtracting the step response of an image without edge enhancement from images with selected settings of edge enhancement and measuring the resulting peak-to-peak differences. These values were then normalized by the step size. Sharpness was characterized by observing the normalized modulation transfer function (MTF) and computing the spatial frequency at 50% MTF. The noise was measured on the gray patches and computed as a weighted sum of variances from the luminance and two chrominance channels of the pixel values.ResultsThe measured levels were consistent with the level set via the user interface on the video processor and varied typically from 0 to 1.3. Both sharpness and noise increase with larger levels of edge enhancement with factors of 3 and 4 respectively.ConclusionsThe presented method overcomes the issue of vendors expressing the level of edge enhancement each differently in arbitrary units. This allows us to compare the effects, and we can start exploring the relationship with the subjectively perceived image quality by medical professionals to find substantiated optimal settings.