The Concept of Homomorphic Filtering

Question

I am trying to understand the concept of homomorphic filtering, I have read several online pages about this topic such as http://en.wikipedia.org/wiki/Homomorphic_filtering However, I noticed a scarce online resources that discuss this topic. Therefore, I have two questions.

First, I am wondering, how one can decide that an image can be enhanced using homomorphic filtering? In other words, what is the type of images that require homomorphic filtering?

Second, is homomrphic filtering always used to attenuate the illunimation (low frequency) and increase the reflectance (high frequency)? Or it can be also used to do the opposite (attenuate reflectance and highlight illunmiation)?

Sadly The Travelling Salesman's problem is believed, with good evidence, to be unsolvable in polynomial time, so you're going to wait a long time for a solution. (Sorry, couldn't resist the joke). — High Performance Mark, Apr 11 '13 at 07:32
People with limited imagination like you believes it cannot be solved in polynomial time. — Traveling Salesman, Apr 11 '13 at 09:28

score 3 · Accepted Answer · answered Apr 11 '13 at 14:56

After further research, I found the answer,

1- Images that are useful to be enhanced using homomorphic filtering, are images where the illumination is distributed unequally causing the objects in the image to appear in a dark color. In general, these images are dark and so their details are hidden.

2- According to this source, Homomorphic filtering is a frequency domain filtering process that compresses the brightness (from the lighting condition) while enhancing the contrast (from the reflectance properties of the object).

the link referenced to is a dead link – Jeru Luke May 27 '17 at 09:49 — Jeru Luke, May 27 '17 at 09:49

score 1 · Answer 2 · edited May 23 '17 at 10:32

Given the fact that homomorphic filtering can be used to split low-frequency illumination and high frequency reflectance from an image, an obvious use of this is in change detection. In change detection, when we compare two images we look for changes in high frequency reflectance part. If we filter away the low frequency illumination part away, that helps.

After homomorphic filtering, the bright input image on the left yields the one on the right.

bright input image output image