I need a way to present data on an essay written about image sharpening algorithm. So I've thought that if I measure a factor of sharpness from image or relative sharpness (between test img and reference img) and another factor like PSR for noise, then I could analyze resultant data with maths and build the essay around that. Is it the right approach to measure image properties? I'm novice when it comes to photography and graphics so any kind of help is much appreciated.
My guess would be that making an image sharper translates into a spectrum that have more high frequency and less low frequency: i.e. the weighted median frequency would increase. Now you can define a relative measure of image sharpness.
To get an absolute measure of image sharpness, you need to define what is maximum and minimum sharpness, and find a way to assign a value in this scale to any image.
There is probably multiple ways to define what sharpness is though. Also, you might want to learn about acutance
Some references on image sharpness metrics:
- Encoding Visual Sensitivity by MaxPol Convolution Filters for Image Sharpness Assessment, IEEE Transactions on Image Processing, 2019
- A Fast Approach for No-Reference Image Sharpness Assessment Based on Maximum Local Variation, IEEE Signal Processing Letters, 2014
- Image Sharpness Assessment Based on Local Phase Coherence, IEEE Transactions on Image Processing, 2013
- $S_3$: A Spectral and Spatial Measure of Local Perceived Sharpness in Natural Images, IEEE Transactions on Image Processing, 2012