Hi Juan,
Please recall the reason for adding the NOISE00 keywords: SA interpolation changes noise statistics. Eg., reference frame noise nearly unchanged (due to near identity homography), but noise of all other frames decreases due to bilinear interpolation. Example:
On a dim project with low scale, I note a similar problem with the scale estimator: bilinear interpolation reduces scale significantly. Results are improper image scaling and loss of SNR.
Other scale estimators (eg., Sn) exhibit the same issue.
Note: this problem was discovered by my new II SNR tool.
Please recall the reason for adding the NOISE00 keywords: SA interpolation changes noise statistics. Eg., reference frame noise nearly unchanged (due to near identity homography), but noise of all other frames decreases due to bilinear interpolation. Example:
noiseMRS | _c (calibrated) | _c_r (aligned) |
reference frame | 2.814e-04 | 2.813e-04 (nearly unchanged) |
a non-reference frame | 2.938e-04 | 1.833e-04 (decreased) |
On a dim project with low scale, I note a similar problem with the scale estimator: bilinear interpolation reduces scale significantly. Results are improper image scaling and loss of SNR.
sqrt(BWMV) | _c (calibrated) | _c_r (aligned) |
reference frame | 4.762e-04 | 4.764e-04 (nearly unchanged) |
a non-reference frame | 4.929e-04 | 3.669e-04 (decreased) |
Other scale estimators (eg., Sn) exhibit the same issue.
Note: this problem was discovered by my new II SNR tool.