I\’m trying to find ways to salvage images that contain oversaturated standards in them (40% and 80% white spectral standards to be exact, 80% oversaturates in both visible and UV images, 40% oversaturates in UV images). By \”salvage images\”, I mean to make them analyse-able in the software and yield the same results that non-saturated images would. Using the oversaturated standards for calibration is a no-go, since it constantly yield significantly larger results in visible R channel compared to that of non-saturated photos (as the warning message said when generating mspec with oversaturated images). I tried to use 10% standard from a separate photo (with same camera setting and lighting) and use that to calibrate the said oversaturated images (and not using any of the 40 or 80 standards for calibration). However, the results are several times in magnitude than those from non-saturated images calibrated using the same 10% standards from a separate photo. All comparisons between saturated and non-saturated images are made when measuring the same object, same position, same lighting as well as camera setting. Only variable would be saturation level. Is there any potential solutions to try out before having to retake the photos with 10% standards?
Hi Nora! From what I understand the pictures are oversaturated quite substantially (i.e. 40% upwards). The problem is not so much the standard, but the fact that it is indicative that any information in your images above 40% reflectance is unreliable/lost. As such, I’d recommend retaking the pictures with lower exposure and exposure bracketing to help reduce the chances of oversaturated images. Unless, of course, you sare certain that the images/subjects do not contain any reflectance values above 40% (I think the screening tool can help investigate that). In that case, indeed, if everything is identical and you have suitable standards at an unsaturated reflectance value, you should be able to go ahead with caution. I would err on the side of retaking the pictures.
Sorry to not have any better news.