Image Quality Factors (Key Performance Indicators) - Imatest

Sharpness

Sharpness is arguably the most important single image quality factor: it determines the amount of detail an image can convey. The image on the upper right illustrates the effects of reduced sharpness (from running Image Processing with one of the Gaussian filters set to 0.7 sigma).

Device or system sharpness is measured as a Spatial Frequency Response (SFR), also called Modulation Transfer Function (MTF). MTF is the contrast at a given spatial frequency (measured in cycles or line pairs per distance) relative to low frequencies. The 50% MTF frequency correlates well with perceived sharpness— much better than the old vanishing resolution measurement, which indicated where the detail wasn’t.

Sharpness and MTF are introduced in Sharpness: What is it and how is it measured?

The perceived sharpness of a print or display is measured by Subjective Quality Factor (SQF) or Acutance, which are derived from MTF, the Contrast Sensitivity Function of the human eye, and viewing conditions.

Imatest‘s primary sharpness measurement uses slanted-edge patterns analyzed by SFR, Slanted-edge SFR (a part of Rescharts), SFRplus, eSFR ISO , SFRreg, or Checkerboard (the latter four are highly-automated), using targets you can purchase or print with the Imatest Test Charts module. Concise instructions are found in How to test lenses with Imatest.

Several alternative patterns, which cause cameras to apply differing amounts of sharpening and noise reduction, can be used for measuring MTF. All require more real estate than the slanted-edge. They include

• Log Frequency, which uses a sine pattern chart that increases in frequency logarithmically. It provides a check on the slanted-edge method. More direct but less accurate,
• Log F-Contrast, excellent for examining loss of detail due to noise reduction,
• Star Chart, a multi-directional sinusoidal pattern,
• Random/Dead Leaves, which measures texture sharpness. The Scale-invariant random pattern minimizes sharpening and maximizes noise reduction. The Dead Leaves pattern is more representative of typical images.

The MTF Measurement Matrix compares the different methods.