제목 | Correcting nonuniformity in slanted-edge MTF measurements |
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작성일자 | 2022.03.25 |
Correcting nonuniformity in slanted-edge MTF measurements
Uncorrected nonuniformity in a slanted-edge region of interest can lead to an irregularity in MTF at low spatial frequencies. This disrupts the low-frequency reference which used to normalize the MTF curve. If the direction of the nonuniformity goes against the slanted edge transition from light to dark, MTF increases. If the nonuniformity goes in the same direction as the transition from light to dark, MTF decreases. To demonstrate this effect, we start with a simulated uniform slanted edge with some blur applied. Then we apply a simulated nonuniformity to the edge at different angles relative to the edge. This is modeled to match a severe case of nonuniformity
Here is the MTF obtained from the nonuniform slanted edges: If the nonuniformity includes an angular component that is parallel to the edge, this adds a sawtooth pattern to the spatial domain, which manifests as high-frequency spikes in the frequency domain. This is caused by the binning algorithm which projects brighter or darker parts of the ROI into alternating bins.
Compensating for the effects of nonuniformity
When this box is checked, a portion of the spatial curve on the light side of the transition (displayed on the right in Imatest) is used to estimate the nonuniformity. The applied compensation flattens the response across the edge function and significantly improves the stability of the MTF: Summary
While this is a large improvement, the residual effects of nonuniformity remain undesirable. Because of this, we recommend turning on your ISP’s nonuniformity correction before performing edge-SFR tests or averaging the MTF obtained from nearby slanted edges with opposite transition directions relative to the nonuniformity to reduce the effects of nonuniformity on your MTF measurements further. Detailed algorithm
k1 and k2, are estimated using the light side of the transition starting at a sufficient distance dN from the transition center xcenter, so the transition itself does not have much effect on the k1 and k2 estimate. To find dN we first find the 20% width d20 of the line spread function (LSF; the derivative of the edge), i.e., the distance between the points where the LSF falls to 20% of its maximum value.
If the edge response for x > dN has a sufficient number of points, it is used to calculate k1 and k2 using standard polynomial fitting techniques. The result is a more accurate representation of the edge with the effects of nonuniformity reduced. Future work
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이전글 | Selecting SFR edge regions based on field distance |
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다음글 | Making Dynamic Range Measurements Robust Against Flare Light |