What is angular resolution?

[21joanna12]

The Wikipedia definition of angular resolution is 'Angular resolution, or spatial resolution, describes the ability of any image-forming device such as an optical or radio telescope, a microscope, a camera, or an eye, to distinguish small details of an object, thereby making it a major determinant of image resolution.'

I get this definition, however it seems to me like the definition of plain 'resolution'. Are there more different types of resolution? And if so, how do they differ?

Thank you in advance :)

 

[Khashishi]

Methinks you are reading too much into it, and it means exactly what it sounds like. It's resolution measured in angle units, as opposed to resolution measured in some linear measure like dots per inch.

 

[Drakkith]

Yes, you can turn angular resolution into, say, resolution in pixels, fairly easily if you know the angular resolution of the imaging system and the size of the pixels on the imaging sensor.

 

[Andy Resnick]

<snip> Are there more different types of resolution? And if so, how do they differ?

Analysis of imaging systems is often simplified by describing the system in terms of angles from the optical axis rather than distance form the optical axis, especially when the objects are very far away. Converting from angles to linear distances at the image plane is generally straightforward.

There are multiple measures of 'resolution' (e.g. Rayleigh, Sparrow, Dawes...), but the essential concept is the ability to distinguish 2 closely spaced objects.

http://www.google.com/url?sa=t&rct=...KpA6KlgKnxyHYIw&bvm=bv.83640239,d.aWw&cad=rja

 

[sophiecentaur]

the essential concept is the ability to distinguish 2 closely spaced objects

When the term 'resolution' was first used, it referred to optical systems using the eye as the receptor. The Rayleigh Criterion was a fairly arbitrary criterion and assumed that two angularly small objects (stars etc) could be said to be resolvable if the dip in brightness between the two images went to half. That assumed that the brightness of the images (signal level) was enough to be able to detect that 'dip'. In practice, it's down to Signal to Noise Ratio, whether you can see the dip or not. With modern sensors and signal processing, the noise can be reduced by filtering and you can detect a much shallower 'dip' allowing you to resolve much better than the Rayleigh Criterion would suggest.