Abstract
Modulation transfer function (MTF) evaluation in the imaging of the optical lenses with poorly corrected geometric distortion involves sampling region of interest (ROI) images that are affected by geometric distortion, reducing its accuracy. A based liquid-crystal-device MTF (LMTF) method is proposed for this purpose by evaluating MTF of the medical rigid endoscope. This method establishes a mathematical model of geometric distortion and analyzes two sampling ROI image manners in MTF evaluation. Compared with the distortion factor (DF) manner, the distortion correction manner relaxes the value of the DF to twice the maximum non-distortion value, extends the sampling ROI image to twice the size, reduces the average RRMSE value to 6%, and improves average accuracy on MTF by 1.2%. The experimental results provide good agreement with the theoretical prediction. Therefore, the proposed LMTF method can be referential for the other optical lenses with poorly corrected distortion.
Highlights
Medical rigid endoscopes (MREs) consist of three parts of optical lenses: the objective lens, the relay system, and the eyepiece
As distortion factor (DF) value is between α and 2 × α, that is, the matrix size of the sampling region of interest (ROI) image within the range of 44 × 44 and 90 × 90, their modulation transfer function (MTF) curves obviously drop at lower frequencies, and their RRMSE values rise to 8.2% to 11.7% (10.1% on average)
The size of the valid sampling ROI image based on the DF manner is limited to the size, where DF value is equal to α
Summary
Medical rigid endoscopes (MREs) consist of three parts of optical lenses: the objective lens, the relay system, and the eyepiece. The wider FOV makes the magnification no longer constant, so the output image loses the similarity with the input target and presents geometric distortion, reducing the accuracy of modulation transfer function (MTF) evaluation. The wide FOV presents images with non-uniform illumination distribution and field curvature. The non-uniform illumination distribution contributes to slight difference on the MTF evaluation before and after illumination compensation.[1] Field curvature can cause the image to be blurred, because field curvature cannot make the center and edges of the FOV clear at the same time. Williams and Burns[3] used a slanted edge gradient SFR method to measure the MTF of the distorted edge images. It may cause the MTF evaluation to be affected by the inappropriate sampling ROI images, reducing the accuracy
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