Camera Resolution and Distortion: Advanced Edge Fitting

Abstract

A frequently used method for camera imaging performance evaluation is that based on the ISO standard for resolution and spatial frequency responses (SFR). This standard, ISO 12233, defines a method based on a straight edge element in a test chart. While the method works as intended, results can be influenced by lens distortion due to curvature in the captured edge feature. We interpret this as the introduction of a bias (error) into the measurement, and describe a method to reduce or eliminate its effect. We use a polynomial edge-fitting method, currently being considered for a revised IS012233. Evaluation of image distortion is addressed in two more recent standards, ISO 17850 and 19084. Applying these methods along with the SFR analysis complements the SFR analysis discussed here.

Camera System Performance Derived from Natural Scenes

“…In the latest iteration of sfrmat, sfrmat4, a higher polynomial fitting can be applied to the extracted edge profile, rather than a linear fitting. This reduces the error when measuring curved edges caused by lens distortion, [22] and is especially useful when measuring SFRs from edges in captured scenes, which are commonly curved. We currently use a 3rd order polynomial fitting function.…”

Updated Camera Spatial Frequency Response for ISO 12233

“…This causes a reduction in the e-SFR due to an effective widening of the estimated edge profile. 13 In this situation, we have two characteristics interacting. The curvature of the edge (distortion) is introducing (bias) error into the e-SFR measurement.…”

“…One way to decouple the distortion from the edge microstructure is to apply a polynomial, rather than a linear model to the edge location data. 13…”

Temporal MTF evaluation of slow motion mode in mobile phones

“…MTFs from both horizontal and vertical slanted edge patches are calculated using the e-SFR slanted-edge algorithm complying with ISO12333 standards. The MATLAB implementation of this algorithm named "sfrmat4" by Burns et al is available open-source [8,9]. Edge patches are fed into the algorithm in RGB color space which is later to be converted to luminance channel using default color channel weights.…”