The first part of this tutorial looked at GIMP desaturate to convert to grayscale, the second part investigated using the Channel Mixer to decompose to grayscale with varying contributions from red, green, and blue, and the third part looked at decomposing an image into its constituent color channels in various modes.
This part of the tutorial will focus on a couple of semi-automated methods for converting to black and white, as well as utilizing GIMP layer blending modes.
The rest of the tutorials in this series are here:
I was fortunate enough on a recent family trip to stay in a vacation home in Kissimmee, FL for a week. We had passes to Disney, and made good use of them. With kids, though, late nights were not going to be possible.
Luckily for me, on the drive to the house itself, there was a rather large property off the road that was surrounded by a wall that was just barely containing some wild overgrowth. Obviously an abandoned property, it piqued my interest enough to have me take a quick gander at Google maps to see what lay beyond the wall.
In the first part of this tutorial we had a look at using the Desaturate command to convert images to grayscale. The second part of this tutorial examined the use of Channel Mixer to adjust the contributions of each Red, Green, and Blue channel to the final grayscale result. This part of the tutorial will focus on decomposing the entire image to its component parts for (possibly) further manipulations.
The rest of the tutorials in this series are here:
To get a good grasp of what we are about to do, it helps to remember the very first part of this tutorial when we looked at what goes into producing a color pixel on your screen (you remember the R, G, B sub-pixels, right?).
In the first part of this tutorial we had a look at using the Desaturate command to convert images to grayscale, and how the different options in that command work to produce their results.
The rest of the tutorials in this series are here:
We saw how the Desaturate command can use straight numerical evaluations for conversion (Lightness and Average) as well as using the relative luminosity model for how our eyes will perceive brightness based on color.
This is a long topic, so to keep you from wanting to put your eyes out with a spoon, I’ve tried to break things up a bit. In this first part, I’ll look at using the GIMP Desaturate command to reduce your images to grayscale and to hopefully shed some light on just how the options calculate exactly what level of gray each pixel should be.
The rest of the tutorials in this series are here:
My hope was to be able to expose some new and interesting ways to approach black and white processing in GIMP, and to give everyone a single point of reference to compare the results to.
The challenge base image
I had originally envisioned it as a sort of contest where everyone could vote on their favorites at the end, but it became cumbersome to maintain entries across Flickr and gimpchat.com. So instead I’ve left the posts as they are to hopefully help others to get a look into some cool ways to approach B&W conversions.
I was thinking that this might be a good image to test against because there is bright, just about blown, sunlight on the side of the house, while there are also very dark shadows in some of the windows and bushes. Hopefully a nicely challenging range of luminance and detail to work with!
There were some great responses from everyone who took a stab at it (pun intended - it is Halloween here!). I just wanted to take a moment to highlight a few of the images/processes that I liked personally…
Over in the GIMP users group on Flickr, there has been a recurring challenge where a theme is chosen, and members will post images based around that theme. Then the users will all vote and choose their favorite, and the winner gets to choose a new theme. It’s usually quite fun, and you get to see some really neat photos from other users.
I’ve been reading through a ton of hyperbole about Adobes Photoshop “Content Aware Fill” for some reason lately (“magical”, “incredible”, “amazing” and others are fun to read).
I don’t think I would be too far off in assuming that Adobes implementation is likely based off the wonderful work of Dr. Paul Harrison. Dr. Harrison’s PhD thesis just happened to yield the code that gave GIMP users the Resynthesizer plugin, which has provided us a “Content Aware Fill” for quite a while now (since before 2005).
If you’ve ever spent any time with the Clone Tool or Heal Tool in GIMP, and haven’t tried out Heal Selection with Resynthesizer, then you might find the results of this filter very helpful.
One of my other hobbies besides photography happens to be web programming. I’ve been doing it in one form or another for many, many years (anyone else remember the first time animated .gifs were cool?). As a hobby it has been a ton of fun, and many of the newer capabilities just make it more so.Anyway, in case you hadn’t noticed I at least took the time to use interesting and pretty font faces on this site (in my opinion). It was literally hours of agonizing over different choices, weights, faces, readability, etc. I finally settled on two main fonts for this site that I thought worked reasonably well together:
Reddit user Janne mentioned in a post of mine about the idea of “Averageness”, and linked to the Wikipedia page describing it. This got me thinking about trying these commands on something like faces.
So I needed a set of faces that were all semi-similar enough to create good averages with. Well, if you haven’t seen the work of photographer Martin Schoeller you are missing out! He has a series of close-ups that are shot with very similar lighting styles and compositions of famous people (and not-famous), that is simply mesmerizing to see.
So I grabbed some random images to try this out with:
