Tag Archives: michelson contrast

What is Resolution?

In photography Resolution refers to the ability of an imaging system to capture fine detail from the scene, making it a key determinant of Image Quality.  For instance, with high resolution equipment we might be able to count the number of tiny leaves on a distant tree, while we might not with a lower-res one.  Or the leaves might look sharp with the former and unacceptably mushy with the latter.

We quantify resolution by measuring detail contrast after it has been inevitably smeared by the imaging process.  As detail becomes smaller and closer together in the image, the blurred darker and lighter parts start mixing together until the relative contrast decreases to the point that it disappears, a limit referred to as  diffraction extinction, beyond which all detail is lost and no additional spatial information can be captured from the scene.

Sinusoidal target of increasing frequency to diffraction limit extinction
Increasingly small detail smeared by the imaging process, highly magnified.

The units of resolution are spatial frequencies, the inverse of the size and distance of the detail in question.  Of course at diffraction extinction no visual information is captured, therefore in most cases the criteria for usability are set by larger detail than that – or equivalently at lower frequencies.  Thresholds tend to be application specific and arbitrary.

The type of resolution being measured must also be specified since the term can be applied to different physical quantities: sensor, spatial, temporal, spectral, type of light, medium etc.  In photography we are normally interested in Spatial Resolution from incoherent light traveling in air so that will be the focus here.

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COMBINING BAYER CFA MTF Curves – II

In this and the previous article I discuss how Modulation Transfer Functions (MTF) obtained from every color channel of a Bayer CFA raw capture in isolation can be combined to provide a meaningful composite MTF curve for the imaging system as a whole.

There are two ways that this can be accomplished: an input-referred approach (L) that reflects the performance of the hardware only; and an output-referred one (Y) that also takes into consideration how the image will be displayed.  Both are valid and differences are typically minor, though the weights of the latter are scene, camera/lens, illuminant dependent – while the former are not.  Therefore my recommendation in this context is to stick with input-referred weights when comparing cameras and lenses.1 Continue reading COMBINING BAYER CFA MTF Curves – II

The Units of Spatial Resolution

Several sites for photographers perform spatial resolution ‘sharpness’ testing of a specific lens and digital camera set up by capturing a target.  You can also measure your own equipment relatively easily to determine how sharp your hardware is.  However comparing results from site to site and to your own can be difficult and/or misleading, starting from the multiplicity of units used: cycles/pixel, line pairs/mm, line widths/picture height, line pairs/image height, cycles/picture height etc.

This post will address the units involved in spatial resolution measurement using as an example readings from the popular slanted edge method, although their applicability is generic.

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