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I've been using my new Aerochrome filter set a lot these past weeks. It produces really articulate colors. At a point that I don't think the original film necessarily did better. (plus digital offers a completely different dynamic range, making digital IRG photos very disctinct from the OG) Until now I haven't noticed any plant health information that isn't distinguishable with the naked eye : young leaves and show pink, older leaves red and the more they wither the more the lean toward orange brown and yellow until it is completely dry and shows grey. My guess is that aerochrome is not intended to be properly white balanced like I do with my photos, and that therefore it shows a strong dichotomy beetween cyan dead plants and pink healthy plants. It is maybe easier to tell the different beetween cyan and pink that beetween grey and green. So yes from what I've seen nothing special is reavealed, it's just way more beautiful than the usual boring green. So to recap my setup for these pictures is : filters : Midopt TB550/650/850 + Lee "Flesh Pink" + GRB3 (+Cokin diffusion filter on some shots) Camera : full spectrum Canon 1200D The channels are swapped in darktable, no IR substraction is needed. I work from sRGB jpegs. No color edits at all. I edit the contasts in Lightroom.

The following experiments are inspired by the findings of @Christoph Here is a series of pictures with my full spectrum canon 1200D and a stack of these three filters : Midopt Triple bandpass 550/660/850nm Lee "Flesh pink" gel GRB3 from Tangsinuo The transmission curve of the three filters combined should look something like this : Both the green and the IR spike are heavily filtered. When the TB is used alone, it seems to suffer from a very weak red transmission : without the GRB3 the red channel records as much (if not more) IR than red, requiring IR subtraction of 100%. The green spike transmission to the contrary is very powerful. To the eye (at least mine) the filter is green. I'm not sure how bright humans are able to percieve red at 660nm, its pretty deep already. I then decided to reduce the transmission of IR and green equally to give room for the red transmission. The GRB3 is used to minimise IR contamination in the RED channel and the Lee gel is used minimise green contamination in the blue/IR channel and to make it more or less match the level of output of the red channel. The blue channel stays very underexposed compared to the two others, and is brought back in white balance (pretty extreme : lower than 1900Kelvin). The exposure value with these filters ranges from 1/50s to 1/100s in sunlight at f5.6, 200iso. It's a very dark combo. All the pictures are channel swapped in Resolve from the camera Jpegs, the process is video ready. No saturation was added and zero IR substraction is needed. The fact that IR transmission is cut by 90% by the GRB3 causes some green leaks to be percieved in the Blue/IR channel. This leads to the need to apply a hue correction to the sky in order to make it look properly blue and not purple-ish. This process is simple and non-destructive. The original color of the sky after channel swap : Important notice : The channel swap causes a significant decrease in contrast and micro-contrast. For a moment I thought this was due to the Jpeg compression but it is not. Do you remember this law ? Y = 0.1 Blue + 0.6 Green + 0.3 Red It is actually crucial in understanding why the images look better unswapped. It describes how the human eye is sensitive to luminosity. The green value is far more decisive in the percieved brightness of an object than the red and blue values. A quick exemple Unswapped image : Swapped image : it looks less detailed and dynamic. The contrast beetween the bright grass and the dark trees is lessened Swapped image but with the "preserve luminance" box ticked : the image is sharper and more alive. (Click on the image and use the viewer to compare both instantaneously.) Explanation : The grass in the unswapped image appears turquoise. Let's make it cyan for the sake of clarity. The trees appear blue. Cyan RGB values are (0; 255; 255) Blue RGB values are (0; 0; 255) The minimum luminance(Y) is 0 and the maximum luminance is 1. Y(cyan grass) = 0.1x Blue(255/255) + 0.6x Green(255/255) + 0.3x Red(0/255) = 0.7 Y(blue trees) = 0.1 x B(255/255) + 0.6 x G(0/255) + 0.3 x R(0/255) = 0.1 in the unswapped image the contrast beetween the brightness of the trees and the grass is important : Y=0.1 versus Y=0.7. Now, let's do the same for the swapped image where the grass is magenta and the trees are red. Y(magenta grass) = 0.1 x B(255/255) + 0.6 x G(0/255) + 0.3 x R(255/255) = 0.4 Y(red trees) = 0.1 x B(0/255) + 0.6 x G(0/255) 0.3 x R (255/255) = 0.3 in the swapped image the contrast beetween the brightness of the trees and grass is less important than in the original image (Y=0.3 versus Y=0.4) In this chart the colors are ranked by luminance. white Y=1, yellow Y=0.9, cyan Y=0.7, green Y=0.6, magenta Y=0.4, red Y=0.3, blue Y=0.1, black Y=0 As you can see here the brightness of Magenta and Red is very close as opposed to cyan and blue that are very far apart. So that's why channel swapping sometimes makes the image lose quality. A solution to this is to tick the box "preserve luminance" in the channel mixer. It doesn't work in every situation since it makes the yellow objects turn way darker, leading to an unnatural look. Ticking the box also makes the sky way brighter. It's a tradeoff that has to be made for each individual picture. In the selection I posted above, a few have the box ticked and most don't.

Hello, There was a nice opportunity to take pictures a morning during Ascension's Week End last May. The shots were done in Aerochrome emulation using @Christoph's combination of Hoya X1 Green + Tiffen #16 Orange filters. The amount of IR is more reduced compared to using a Tiffen #12 only, but with the advantage of not saturating the images too much. Processing was done using Rawtherapee. Photographs were taken using a Canon EOS 6D Full Spectrum paired with a Nikon 50 mm F/1.8D : 1. ISO 160, 1/250s, F/5.6 or 8. These buildings seem straight out of one of Philip K. Dick's novels (Ubik). 10-15 years ago it was tall grass and abandoned factories. 2. ISO 160, 1/250s, F/5.6 or 8 3. ISO 160, 1/250s, F/5.6 or 8. The tower's construction started in October 2021 and is nearing completion now. 4. ISO 160, 1/250s, F/5.6 or 8. 5. ISO 160, 1/250s, F/5.6 or 8. This metallic sculpture is an homage to Gustave Eiffel, who was born here (Dijon, France). 6. ISO 160, 1/250s, F/5.6 or 8.

Editor's Note: I split off the discussion of the Collodion emulation from OlDoinyo's original 2014 topic Ultraviolet as a Tool for Faux-Vintage Effects. good morning, after a year I return to update you. I bought a full spectrum A7; my idea was to use it with Schott BG25 filter to emulate the wet collodion spectrum that "sees from 325> 510nm" But there is a big problem ... the sensor sees many I.R. so I ordered a BG39 (similar to s8612) I hope it works ... to have a preview of the result and the right exposure when I take pictures with the collodion. I have a doubt. Will BG25 + BG39 be enough? in the graph of the schott that I have elaborated, you can see the green part that is cut however there is a zone that I have marked in red from 1300 to 3000 nm that exceeds 1 percent. I ask you: do you know how far you see the sensor of the sony A7 F.S. ?

Digital Daguerreotype, I have been wanting to do this for years.... While I was waiting for electricity to come back into my life.....24 hours without.....I went looking into a secret cache of small, 25mm filters I purchased from Omega years ago. One caught my eye......390-530nm.....all in the cool colours range, nice for a Digital Daguerreotype, I thought. So onto the O D Industries 50mm lens & outside we go... Cool Spectrum in Colour. Cool Spectrum in B&W.

There has been increasing interest recently in photographic techniques that render foliage in some shade of red rather than the more familiar green. Unquestionably, this has been inspired by the existence (and more recent demise) of certain Kodak infrared films which did this as a consequence of their engineering. A number of techniques have been devised which do this to some extent or another, some involving infrared light and others not. It is beyond the scope of this post to describe all of these, but one of the oldest of them is to construct an image using the same cross-sampling scheme as the old films, termed an IRG image. There are, in turn, two ways of going about this: combining information from separate infrared and visible images of the same scene (the two-exposure method) or taking a single exposure through a sharp-cutoff filter, isolating the infrared signal in the "blue" channel, and performing a combination of channel transposition and signal subtraction to construct the final image (the single-exposure method.) There are drawbacks to either approach--the two-exposure method is precise and conceptually simple, but often unwieldy and somewhat limiting in practice. The single-exposure method is more complex and more approximate, but much easier to deal with at the camera stage. A rival paradigm gaining some currency of late is the IGB image, which can be constructed by the above two-exposure method (and will be below) but in practice is more often obtained with a converted camera and a special filter or stack of filters and a single exposure. Conceptually, this involves replacing the red channel of an ordinary visible image with an infrared exposure. Advocates of this method point out that the image looks as it does straight out of the camera, without the need of extensive processing, and that it lends itself more easily to video use than the other.. These two image types have both similarities and differences. To illustrate, a test scene was chosen which contained: -foliage; -a car taillight; -red and green LED signage; and -red painted surfaces. Here are the constituent RGB and infrared images used in this comparison: And here is the 2-exposure IRG frame of the scene as constructed, with minor post-processing: In addition to the reddish-pink foliage color, one can see other signature characteristics of an IRG image. The red painted surfaces and car taillight now show yellow, due to the reflection of both red and infrared. The red LEDs now appear green(ish) and the green LEDs appear blue. The sky is somewhat obscured by chronochromic fringing due to cloud movement, but the top shows the characteristic deeper blue color, less green than in an RGB image. Here is the two-exposure IGB image of the same scene: As initially constructed, due to the large amount of green light coming off the foliage, the vegetation appears orange rather than red, and the sky is more cyan than in the other images. Substantial hue adjustments were necessary to make the image more similar to the other. I do not own the relevant filters myself, but it is interesting to note that some users of filter stacks have also reported vegetation coming out more orange than expected. In passing we note that the red painted surfaces and taillight remain red and the green LEDs remain green. The red LEDs are blacked out. It is not the aim of this post to claim that one image type is inherently superior to the other; artistic taste is a matter of opinion and there is no right or wrong here. Rather, it is hoped that the difference between the image types will have been clearly enough elucidated that informed choices are made possible.