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Digital Phantom Leaf Photography (Read 49631 times)
Bruce Moen
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Digital Phantom Leaf Photography
Mar 19th, 2012 at 11:39am
 
For a number of years I have been working, off and on, on a project I now call digital phantom leaf photography. It is a modern, no-voltage, simplified variation of the old kirlian photography technique.

Recently I began learning how to use imageJ software and I am struggling to learn enough Java to teach myself how to write plug-ins for my project.  I am looking for someone or some group who might be interested in providing some plugin writing assistance in this open source project.

When I first began the project I used FilterMeister to write plug-ins for Adobe Photoshop using 8 bit per channel, RGB images.  That work demonstrated that the vein structure of a freshly picked leaf could be seen in a pseudo-colored image of an area in which the leaf had been physically removed.  I have 2 example images I can provide from this previous work that appear to show this phenomenon. In my present work I would prefer to use 16 bit per channel TIF images and Photoshop cannot handle this task adequately. 

Brief Technique Description:
An ordinary digital camera is used to photograph a leaf both before and after a portion of the leaf has been removed. Post-processing of this image uses a lookup table approach to use pseudocoloring as a means of displaying pixel value variation. Previous work shows that the basic approach is workable. I feel that improvements can be made in the plug-in design to provide higher-quality images of the missing or "Phantom" portion of the leaf.

If you know someone or some group that may be interested in working on this Open Source project please have them contact me.

Thank you,

Bruce

PS  I am working on getting the example pictures posted here
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« Last Edit: Mar 26th, 2012 at 5:27pm by Bruce Moen »  
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PauliEffectt
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Re: Digital Phantom Leaf Photography
Reply #1 - Apr 27th, 2012 at 6:08pm
 
Does the work need some skills in Fourier Analysis, as I guess that is needed
for some image treatment? And the second questions is if it needs to be written
in Java? If it needs computation time, C++ should be about a 100 times faster.
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Re: Digital Phantom Leaf Photography
Reply #2 - Apr 29th, 2012 at 10:21am
 
PauliEffectt.
PauliEffectt wrote on Apr 27th, 2012 at 6:08pm:
Does the work need some skills in Fourier Analysis, as I guess that is needed
for some image treatment? And the second questions is if it needs to be written
in Java? If it needs computation time, C++ should be about a 100 times faster.


The software I am using for analysis and display of the results is ImageJ.  ImageJ is Open Source software primarily used in the medical field and it is able to handle 16 bit per channel, TIF files.  It, as well as its plugins, are written in Java, hence the language requirement.

Not sure if Fourier analysis will be required or not, don't know enough about how to apply it to the task.

In my original work I used 8 bit per channel files and PhotoShop.  I taught myself enough C++  for that using FilterMeister to create and run my plugins  The task just involved pseudo coloring the pixel intensity values of the missing leaf portion of the image.  This required that the white background in the image be almost perfectly uniform in RGB pixel intensities.  That not as easy as it sounds, but I managed to get close enough that pseudo coloring the pixel intensity variations brought out the phantom lead vein structures.

In my latest work I want to subtract a reference image of the background from the phantom leaf image taken as an overlay upon the same background.  This should give an image of just the pixel intensity variation due to the phantom leaf.  Pseudo coloring this image should give a clearer, more repeatable resulting image of the phantom leaf.

Right now I am working toward reducing camera sensor noise.

Bruce
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ottawa1
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Re: Digital Phantom Leaf Photography
Reply #3 - May 9th, 2012 at 3:28pm
 
This is some really interesting work Bruce. Please post more pics of other leafs when you get the chance. I too see the veins but they are in positions different to where they should be-very strange stuff so it will be interesting to see if other images also have this same effect.
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Re: Digital Phantom Leaf Photography
Reply #4 - May 31st, 2012 at 5:14pm
 
I was very interested in your work.
I just used my camera, but it is a small basic one with little options. I have no raw possibility; and auto-focus can't de turned off. So I have some slight movements of my picture.

My camera was on the top of a stack of book to focus the leaf (white paper behind the leaf). I used the 2 second delay function to make each picture so the camera could stabilize. I realized 20 pictures, one by one.

I used IRIS software, free software and it can manage picture functions (iris is made for astronomy) like addition, substraction, multiplication of pictures. So I could do the following operations:

1) first realize a median picture with the 20 pictures. This is a reference picture that is like a "background"
2) Then substract this background from each picture: you have the variations
3) Then multiply all these variations to have an amplification
4) And add all these result pictures to have a global picture

I could see nothing, but this is a first approach.

Could you tell me how many pictures you use (and what conditions: rafale mode or one by one) and what operations you do on your pictures please, so I could use a better algorithm?
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Re: Digital Phantom Leaf Photography
Reply #5 - Jun 2nd, 2012 at 11:07am
 
Bruce, have you made any further advances with your leaf photos? Awaiting more of these photos as the previous were very interesting.
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Re: Digital Phantom Leaf Photography
Reply #6 - Jun 21st, 2012 at 9:51am
 
I first thought that you took many pictures of the same leaf and that you computed intensity differencies for the same pixel within the picture sequence; and pseudo coloring thiese differencies.

But when reading again, I think I was wrong: you make the whole study only with ONE picture and compute intensity from one pixel relatively to adjacent pixel?

Could you please explain clearly what you did, because I tried many times to do something but it is impossible to do if I don't know what you did excatly.

What differencies between which pixels? I can write a script too, but I don't know what you did precisely. Thank you for your answer.
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Re: Digital Phantom Leaf Photography
Reply #7 - Jun 21st, 2012 at 1:52pm
 
Pascuser wrote on Jun 21st, 2012 at 9:51am:
. . . But when reading again, I think I was wrong: you make the whole study only with ONE picture and compute intensity from one pixel relatively to adjacent pixel?

Could you please explain clearly what you did, because I tried many times to do something but it is impossible to do if I don't know what you did excatly.

What differencies between which pixels? I can write a script too, but I don't know what you did precisely. Thank you for your answer.

Pascuser,

I am happy to hear from someone interested in experimenting with this fascinating technology and I hope more will join us.  Please feel free to ask more questions and I'll do my best to answer. 

Your are correct about using only one picture, but in my early work I computed  the intensity relative to an arbitrary, constant pixel value, sometimes using a value of 256.  In order for this to work it is assumed that:
1. The white background light intensity is perfectly uniform or very nearly perfect.
2. AND that none of the pixel values in the phantom area of the photo exceed 255.

The method I first used to obtain the phantom leaf images used a single photo.  With this method the actual pixel value in the missing leaf area of the photo was subtracted from an arbitrary, fixed value (often 256) to yield a new value.  This new valve was then used  in pseudo coloring to bring out the phantom leaf structure in the image. 

For example for an 8 bit per channel, RGB (standard JPG file format.) image I chose 256 as the arbitrary  value.  My filter algorithm was then:
New Value = 256 - Actual Pixel Value

The New Value was then used to select a pseudo color from a crude Lookup Table to generate the final image.  It took quite a bit of experimenting with pseudo color selections to make the phantom leaf structure clearly visible.  The picture at the bottom of the page at http://afterlife-knowledge.com/phanpics.html was one of the better of these pseudo color selections.  The vein structure turned out to be dark relative to the surrounding areas.

It is important to understand how critical it is that assumption number 1 above be true in order to obtain phantom leaf structure images.  Ideally, if you took a photo of just the white background, without any leaf, the intensity of EVERY pixel in that image would be EXACTLY the same value as all other pixels of that pixel color.  In other words in an RGB image every red pixel would be the same value as all other red pixels.  Green pixel values can  be different from the red or blue RGB image values, but all green pixels would, ideally be the same value.  Same goes for the blue pixel values in an RGB image of just the white background without any leaf.    

To see how uniform my white background was in my early work I used my filter algorithm to generate a pseudo colored image for each of the RGB pixel colors.  In this way I could verify that my photos later taken with the leaf met that first assumption above.  Then, since the background is uniform intensity I could use an arbitrary value (like 256) in the pseudo coloring of the phantom images.  In those images I was seeing the differences in pixel intensity values that the phantom leaf structure imposed over the previously uniform background intensity.

In practice I found it impossible to create an absolutely perfect, uniform intensity background.  But I didn't start seeing the phantom leaf structures in the pseudo colored images until the white background was pretty close to perfectly uniform.  Probably in the order of (I am guess estimating here) a total range of 5 (out of 256).  The more you can do to make your white background pixel intensity (in an image without the leaf as a test photo)  perfectly uniform the better your chances of getting good phantom leaf photos.

I hope that answers your questions. If not please feel free to ask more.

In my present work I am trying a different approach that uses three photos, but I recommend that experimenters start with the single photo method as it helps you learn about other factors.  For example, how do you chose a leaf?  How soon must the picture be taken after picking?  Depth of field settings?  Illumination light frequencies?

The three photo method is an attempt eliminate the need for a near perfectly uniform background.  The camera must not move AT ALL when taking Photo#2 and #3 using this three photo method.  Use a cable release, or ideally, a remote electronic trigger to trigger the shutter.  If you use your finger to push the camera shutter button the camera will move enough to make this method not work!  Also you MUST lock the aperture, shutter speed and focus to the same place for all three pictures.

Photo #1.
A photo is first taken of the original, intact leaf without a portion removed.  This is a reference photo used later to visually compare the actual physical leaf structure to any phantom leaf structure obtained from the next two photos.  The leaf in this photo must be positioned in the same location (relative to the camera and white background) as it will be in the next photo, that is, Photo #2.  Focus on the leaf, lock that focus, select an appropriate aperture and shutter speed and lock those so they are the same for all three photos.  This method will not work if you fail to do this!

Photo #2
Cut way a portion of the leaf quickly and carefully.  Then take photo #2 without moving the leaf from its location relative to the camera and background.

Photo #3
Remove the entire leaf from its location so that it will not be seen in this photo.  Drop it on the ground is the easiest.  Then quickly take photo #3.  This is an image of just the background.

The algorithm for pseudo coloring in this method obtains the New Value by subtracting the pixel values of Photo#2 from Photo#3.  Since the actual background is the same in both images this subtraction removes the background and any non-uniformity in that background.  It gives a result that is only the background difference induced by the phantom leaf structure.  The background doesn't need to be perfectly uniform because this method subtracts the background from the resulting image.  All that is left to do is to pseudo color that resulting image and visually compare it to Photo#1.

What is taking me so long at this point is that I am trying to do this using 16 bit per channel RAW image files (converted to TIF files) instead of 8 bit per channel JPG files for greater resolution.  There are camera sensor noise issues to deal with as well as writing filter programs to handle these high resolution RAW or TIF images.  I would suggest experimenters use JPG format images (perhaps super fine resolution JPG) if you attempt this method.  Also be careful that your subtraction of the two images does not result in a negative number! Those negative number results are automatically set to zero making them useless.  Little details like that can prevent obtaining phantom leaf images.  Details, details.

Well, like I said at the beginning, I hope this helps answer your questions and I hope more experimenters will join in.

Until there are more questions, or I have some great results to share . . .

Good luck!!

Bruce
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Bruce Moen
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Re: Digital Phantom Leaf Photography
Reply #8 - Jun 21st, 2012 at 2:23pm
 
Pascuser,

Actually, using the median of 20 photos would be a good idea, if the camera, leaf and background were in exactly the same place in every picture with not even slight movement from photo to photo..  Focus, aperture and shutter speed would also have to be exactly the same for all twenty photos for this to work.  And the background piece of white paper would have to be near perfectly uniform for the "single photo method" to work..

The advantage of using a median of 20 photos is that camera sensor noise is most likely reduced in that median image.  Such noise is a confounding factor in obtaining phantom leaf images.

But it sounds like you would need a camera upgrade so you can control all the settings and it would need a cable release or electronic release for the shutter to eliminate movement.  You can probably use a camera that outputs a JPG format image, I'd use the "super fine" setting to get the highest resolution possible.

Your use of the median of multiple images could work well with the "three photo method" I described in my previous, long post.   I use this median image approach as a way of reducing camera sensor noise effects in my present work.

Bruce.
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Re: Digital Phantom Leaf Photography
Reply #9 - Jun 21st, 2012 at 2:36pm
 
ottawa1 wrote on May 9th, 2012 at 3:28pm:
I too see the veins but they are in positions different to where they should be-very strange stuff so it will be interesting to see if other images also have this same effect.

ottawa1,

I have seen the shift of vein structure locations in other phantom images, it is actually pretty common.  Often some or most of the veins are in, or close to, their physical leaf positions with only a few showing large displacements.  I don't know what causes these shifts.  Maybe the "fabric of empty space" they reside in is flapping in some unseen "empty space breeze"   Roll Eyes?

I wish I had the technical horsepower to use videos instead of single images so I could observe this shift over time.   That might yield some really interesting results.

Bruce
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Re: Digital Phantom Leaf Photography
Reply #10 - Jun 21st, 2012 at 4:04pm
 
Just a thought.

I don't know how many of you played with HDR retouching on photographies (tonal mapping, extreme contrast, catalogue-like colorful outlook and so on), but there is one thing to consider. Part of aural picture seen by the eye may be the result produced in the same way as the halo around and between objects on HDR photos, i.e. predictive adjustment/enhancement (augmented reality) in order to make the object better visible for conscious processing. Maybe a good idea would be to think out how our eyes work and how our brain reproduces pictures - representing some kind of pattern connections with artificial addons, which are real not in terms of physical but mathematical and other "(perceptual) agreement based" context. The pictures/reality we see may be rather conceptual than objective, but concepts are also mathematical formulas based on physical modelling, and they can be filtered too, like raw graphic or sound. If you look on your computer screen and watch a movie, then you see something that is real and not real. If you would like to go inside the computer to see where the movie is - you will find nothing similar to screen pictures. But using algos compatible with the platform (computer, operating system) - then you may alter the movie (brightness, contrast, other) on the "conceptual" level so to speak.

Conclusion. It may happen, that visual data produced without agumented reality (without predicting visual representation of context based extended picture) - will remain useless from visual point of view, like the insede of a computer that is showing a movie.
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Re: Digital Phantom Leaf Photography
Reply #11 - Jun 21st, 2012 at 4:30pm
 
I have things to show you, but the system tells me that I can't post pictures and links if I have not more than 3 posts in the forums.

So this post is the third one, I hope next one will be more interesting.
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Re: Digital Phantom Leaf Photography
Reply #12 - Jun 21st, 2012 at 4:31pm
 
Bruce, thank you very much for your complete explanation.
Before I could read you this evening, I did some tests this afternoon (I am not in the same time zone than you here because I live in France).

1) I used a webcam I bought too dayx ago (a used one) with the particularity of great sensitivity, and noise reduction because it is a CCD captor (nowadays webcam have CMOS captor, with a greter noise). Many amateur in astronomy use this webcam for its particularities. It is no more to sell, you can buy it only as used ones. No matter, you probably can have the same results with a classic webcam.

So I put my webcam in front of the leaf, I cut the leaf and used the computer to take 30 pictures. I used color pictures first, and black and white pictures afterwards. What is good with this webcam is that I can get directly CCD pixel informations in a raw format with the free software controling it (IRIS, made for astronomy).

Then as there was absolutely no movement (the computer orders the picture taking with the fixed webcam in front of the meaf)  i could do a median for these pictures.In fact I took 50pictures but as weather was changing, luminosity was changing too and outside luminosity was my only source of light and this had impact in the pictures.

So I could use only 30 pictures with an approximate same luminosity. A stable weather would be a very good condition to achieve the work.

I substracted the median picture from all picture sequences in black and white mode (gray scale in fact) and so I got the noise of each picture as a result (this eliminates the background uniformity). I added this noise of all pictures to get a final picture to use.

I substracted an arbitrary offset with a maximal value less than all values of pixels in the zone to study. Here values were varying from 200 to 220 so I substracted 190. Then I multiplied the values by factor 10, so I have a spread of values. I used a program function to change colors instead of gray levels (visualisation threshold in IRIS) and I could get the following result:
...

The original picture was:
...

I took the picture of the leaf without cutting but not in the same position, so I didn't use it.

I can see something like veins, but this is not sure and not proven with a good picture computation like Bruce wrote in his previous post.

2) I used my numeric photo camera, the bad one with no quality (low price camera). I took only one picture of the leaf (another one, a fresh one, to have more strength in the field to observe) and my camera is able only of JPG format.

So I used JPG format. I then tried to see the differences from one pixel to the other adjacent one.

To do so, I used a derivation in x. This is done with a translation of the picture in x absciss, then you substract from the picture not translated (IRIS can perform all this job and scripting for every function is possible, so you can do many things, a free sotware very powerfull). Then you have as a result an intensity very important for zones with rapid variation and you have black color for no variation. It is an easy way to see variations.

I did it in x, and I could achieve the same result with y derivation.
Then I did the same substraction of offset than for the previous test, with a multiplication to spread the values and visualisation threshold.

I could get this:
...

Starting from that:
...

Here too I see a vein, the vertical one and an other one in the middle, transversal. Whan I say I "see" I want to say that I may see it or not. This is a very basci work, but it demonstrates that basis for Bruce's resultats are not to hard to get.

Now, with the informations Bruce gave us here, I will be able to perform a better job, and maybe I will get as good pictures as his. I will try in any case.

I will inform you here of what I get in my future tests.

Thank you again Bruce for your sharing here and valuable explanations to be able to do it like you.
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Re: Digital Phantom Leaf Photography
Reply #13 - Jun 23rd, 2012 at 4:43pm
 
I designed a small program in Delphi to do all the adequate manipulations. It allows me to load the picture, and to do what Bruce did:

I decide a threshold value for pixel green intensity that allow to detect the background of the hole in the leaf. For every pixel with grenn intensity above this threshold (the background pixels, white approximately) I make a substraction.

I substracted the threshold to the pixel value:

pixel[i,j] green intensity - threshold -> result value green intensity
and the same for blue and gred intensity for the same pixels.

Then I used these result values to colorize the pixels with a random palette I first generated. How? I completed a table with random value between 0 and 255, with three lines: one line of random values for R, one line for G and one line for B.

Then when the result value for a pixel in green intensity is 5 for sample, I take the 5th value on the table in the G line and that defines the new intensity for this pixel.

I have designed a button to click to generate a new random palette of coulours (a new random table) to have another colorizing. Then I can change both the random palette and the threshold value. I take a picture screen capture whrn I have something interesting.

That is what I did.

Now the results:

First, the same pictures I posted in last message computed with this program:
...
...
...

A new experiment done today with another leaf (coming from another tree):

Before I cut a hole in the leaf:
...

For this test I used my Numeric picture camera and I did three pictures: one with the leaf in "good health", one with the same leaf amputed and one without the leaf to have the backgound, picture camera being at the exact same place. But my picture camera changes aperture when it decides and I can't prevent it because it is all automatic (a cheap one). So the background intensity is not the same with the meaf and without (because without leaf, there is a lot of white intensity and the camera automatically changes the aperture to reduce the luminosity).

I got this result, when computing the picture result of the substraction of background picture from the amputed leaf picture:
...

Using the picture taken directly, with no background substraction, and using my program I got (in gray levels here for this test):
...

Now a new experiment with my webcam, another leaf from the same tree. It has the advantage not to have autofocus or else: all is parametrized with software (IRIS here).

I don't know why I did not posted here a picture with background substraction, I only captured the work I did with direct use of my program, with no other background picture used:

In gray levels:
...

With color, another capture and computing of the picture:
...


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Re: Digital Phantom Leaf Photography
Reply #14 - Jun 25th, 2012 at 12:11pm
 
Pascuser,

BIG THANKS for as we say, "taking the bull by the horns," and actually working on this.  You have done quite a bit of work in such a short time!  Your ability to create your own Delphi programs to analyze and display the images is giving some pretty amazing, quick results.  In some of your resulting images I see very clear examples what look like vein structures in the missing leaf area.  Bravo!

I would say that you have accomplished in a few days what originally took me many weeks of trial and error attempts to do.  And your results look as good as any I achieved.  It's exciting to see that this previous work can be replicated so quickly.

I am still wrestling with effects like camera sensor noise in my efforts to obtain clearer images.  I think the three photo method will hep get rid of steady state noise, and averaging multiple images may lower overall random sensor noise.  But only more experimenting will show the way.  Your CCD sensor looks like a good choice from a noise perspective.

I too found that the ability to adjust colorization factors in  the program was helpful.  Sometimes a little shift up or down in the lookup table would change the colorization in a way that would make the phantom structures easier to see.  Likewise, sometimes the adjustments would washout the image making those structures impossible to see  Sad

I feel the field is so new and so much is unknown about what we are photographing that there is much to learn.  And the only way I know to learn is to keep experimenting and exploring, testing theories and learning.

I am also excited by the prospects of seeing further development of these efforts toward more refined and clear images.  That as well as extension into wider areas of exploration.  Who knows?  Maybe these techniques can be used to get images of phantom limbs (missing fingers, arms or legs) or images of the aura surrounding our bodies?  Who knows?

Thank you so much for sharing your work and results.  I hope as these efforts continue others will be encouraged to join in and lend their expertise and curiosity.

Bruce 

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