Decoding Dallas: How They Fooled Us....

[Christian Toussay]

 

 

..Yep. Actually, the image is BIG. You have to get a correct scale of how a person would look like through that window.

I realize that I have been working fro more than 20 years with these images, and which is not he case for casual viewers.

I will post a detoured version asap...

There it is. The star is positioned just above the man's head, giving you a sense of scale:

 

Edited April 26 by Christian Toussay

[Christian Toussay]

1 hour ago, Jean Ceulemans said:

It would be easier if you could indicate what part is being worked on, it´s hard to figure out the size and place of the detail

 

...I've posted a detoured version...

Again, the image is BIG...

 

 

Edited April 26 by Christian Toussay

[Richard Bertolino]

On 4/25/2024 at 5:20 PM, Christian Toussay said:

 

OK, so I am trying to continue this presentation, hoping that now the links will stay: I have modified the Google Pix settings accordingly.

If that works, I will repost the missing images on the precedent files.

The segment on the head wounds established, among other things, that the official record has been tampered with:

- the cavity and bone flaps on top of the head should be seen in the original Moorman picture

- the volcano-shaped occipital exit wound should be seen in the "original" Zapruder film: it doesn't because it has been deliberately blurred

- the occipital wound is actually present in the autopsy picture, and those who testified to the contrary can now be impeached, like those who forged the record

- the frontal entry wound is actually visible in the autopsy picture, and those who did not testify to it can also be impeached

 

There was evidently a massive tampering of the photographic evidence in the case: this could only be done by the immediate and coordinated actions of the Federal Government.

 

How was it done? Let's take  a quite striking example, and at the same time let us solve one of the many collateral mysteries of the JFKA: the "box discrepancy arrangement in the Sniper's Nest", which originates from an evident conflict between 2 pictures of the Sniper's nest, taken by two differents photographers at slightly different times.

To make it short, one (Dillard) shows one box partially visible on the left, while the other (Powell) actually shows a full barricade of stacked boxes lined up across the window. Because of time constraints for Oswald known movements, Conspiracy Theorists see there proof of Oswald's innocence or at least other accomplices involved in moving the boxes. Lone Nutters are not comfortable with this fact, relying on light and shadow tricks to explain it away, not convincingly.

That is where the situation stands as I write this, 61 years after the fact.

Now let's see how this mystery is resolved, thanks to this unconventional, but extremely efficient process I am proposing to the JFK Community.

I post below a version of the Powell picture: it is recorded in my file as  the "Gert Powell Colored Version": I either downloaded it from JFK Lancer or the Robin Unger Gallery.

 

 

 

I post below a version of the Dillard picture: this is known as the "FBI Version", notorious for the ominous black arrow that points at ...nothing:

 

 

So the discrepancy between the two images is clear to see.

So let's see now if the process, which has revealed three assassins in Dealey Plaza and the true nature of JFK's head wounds, can help us here.

As it happens, it can. Below is a processed result from the Powell data bank. Prepare to be angry. Very angry:

 

 

 

 

I post below an intermediate result (remember, the process is iterative: each step in the "cleaning up" of the image under analysis is documented by a specific file), showing the forgery literally "in the making": you can see the fake box contour around the man's head...

 

 

So this is a solid example of one of the technique used by the forgers: just hide unwanted details under " special effects" added to the film or picture of concern.

We will see more of them, but first: I don't know about you, but I am intellectually curious. So this black arrow pointing to nothing in the Dillard FBI version sort of piqued my curiosity. Why would an FBI analyst, studying this image taken in the immediate aftermath of the shooting, put an indicative arrow pointing at...strictly nothing.

 

I will present tomorrow results obtained on the Dillard picture. Again, prepare to be very angry...

 

I'm

 

Edited May 16 by Richard Bertolino

[Richard Bertolino]

I

 

Edited May 16 by Richard Bertolino

[Christian Toussay]

On 4/27/2024 at 1:37 AM, Richard Bertolino said:

I see the "police officer" now. But I don't see how he comes from the original. Can you explain what you did to the original to produce the image of the police officer?

..Hi...

I also posted an intermediate result, actually showing the man into the fake box contour. I don't know if you can see it.

The stack of boxes was simply painted over the original image.

I have explained several times what I am doing, which is very simple methodology I designed to, possibly, retrieve weak signals in finite data sets.

The process has less than 5 operational steps, and does not require any exotic software: any software capable of generating overlays will do.

I will conclude this presentation with a specific thread about the science behind the results shown here. But to answer your question, this is simply about building an ever-increasing data bank of iterations which are crosschecking each other at infinitum via a feedback loop. These are the operational steps:

- 1) select a source image

- 2) create a derivation / new iteration of the source, by using any of the usual optical settings: light, sharpness, smoothness, contrast, texture, whatever; save it

- 3) interpolate (meaning: add, blend, differentiate or multiply) this derivation of the original with the original itself, using the overlay function of your software: you will thus create a new iteration again; save it. You now have two iterations plus the original source in your data bank.

All those iterations, derived from the same source set, are pertinent to how to resolve remaining unknowns within said data set.

You can of course do that ad infinitum. What you will observe is that, because objective information will have a propensity to manifest more frequently and more coherently than artificial data / noise, there will be be a considerable reduction of overall noise (in pictures, this will translate as "blur") and a retrieval of previously weak (or invisible) signals, simply because, once again, if they really represent objective information, they will be more resilient along the process than noise will ever be. .

This explains how purposefully hidden images, invisible to the naked eye, can actually be retrieved and revealed.

In 1998, when I started this research, I could not find anything in scientific papers about what I was doing. In 2014 I actually discovered that a new methodology,

very similar in its concept and operational modalities to what I am doing, had been scientifically acknowledged and called " a major breakthrough".

I will extend on this in the "Science Behind the Results" Thread.

[Christian Toussay]

On 4/26/2024 at 3:17 AM, George Govus said:

@Christian ToussaySo sorry, the most recent links don't work. A shame. Speaking as an artist, I can say the images you have managed to share are very interesting!

I notice there's yet another image hosting service you could try. I see this one allows for hosting a picture indefinitely.

https://postimages.org/

...Thks a lot George, this seems to work...

[Richard Bertolino]

On 4/28/2024 at 2:57 PM, Christian Toussay said:

..Hi...

I also posted an intermediate result, actually showing the man into the fake box contour. I don't know if you can see it.

The stack of boxes was simply painted over the original image.

I have explained several times what I am doing, which is very simple methodology I designed to, possibly, retrieve weak signals in finite data sets.

The process has less than 5 operational steps, and does not require any exotic software: any software capable of generating overlays will do.

I will conclude this presentation with a specific thread about the science behind the results shown here. But to answer your question, this is simply about building an ever-increasing data bank of iterations which are crosschecking each other at infinitum via a feedback loop. These are the operational steps:

- 1) select a source image

- 2) create a derivation / new iteration of the source, by using any of the usual optical settings: light, sharpness, smoothness, contrast, texture, whatever; save it

- 3) interpolate (meaning: add, blend, differentiate or multiply) this derivation of the original with the original itself, using the overlay function of your software: you will thus create a new iteration again; save it. You now have two iterations plus the original source in your data bank.

All those iterations, derived from the same source set, are pertinent to how to resolve remaining unknowns within said data set.

You can of course do that ad infinitum. What you will observe is that, because objective information will have a propensity to manifest more frequently and more coherently than artificial data / noise, there will be be a considerable reduction of overall noise (in pictures, this will translate as "blur") and a retrieval of previously weak (or invisible) signals, simply because, once again, if they really represent objective information, they will be more resilient along the process than noise will ever be. .

This explains how purposefully hidden images, invisible to the naked eye, can actually be retrieved and revealed.

In 1998, when I started this research, I could not find anything in scientific papers about what I was doing. In 2014 I actually discovered that a new methodology,

very similar in its concept and operational modalities to what I am doing, had been scientifically acknowledged and called " a major breakthrough".

I will extend on this in the "Science Behind the Results" Thread.

 

Edited May 16 by Richard Bertolino

[Christian Toussay]

 

Ok, the link prblm is apparently solved.

I will update all preceding threads with those new links.

 

OK, so we've seen that, just as the Ruler's Puzzle in the back-of-the-head autopsy picture, the Powell / Dillard box discrepancy is explained by forgery of the record: in the first case, it was about suppressing the occipital exit wound; in the second case, it was about suppressing the presence of a man in DPD uniform in the Sniper's Nest, about 30 seconds after the last shot.

In both case, Special FX, i.e. the inclusion in the data set of deceptive information was used: fake wet hair to hide the occipital wound, and a stack of box to hide the DPD officer.

That's one method, that we will find again in the Zapruder and Nix films.

But let us see different technique of the forgers. I am reposting below (not sure it is still accessible here) the Dillard picture:

 

 

As captioned, this is an FBI document, so the black arrow pointing at nothing intrigued me. So I decided to also processed, just in case, the Dillard picture.

 

I post below a result from that processing:

 

 

And here are two different iterations from the data bank:

 

 

 

 

So this is the fourth picture, so far, being presented here of a man wearing a DPD uniform present in the Sniper's Nest from 10 minutes before (Bronson film) to 30 seconds after (Dillard / Powell) the shooting, all this data coming from different material, different point of view and different time sequences.

That's quite a lot of corroborative data.

But the discovery of this man does not actually resolve the mystery of the FBI Arrow.

As I am about to post, I realize I can't locate the files I wanted to present about the solution to this Arrow problem....

So this is what I'll do; I will use the processed result posted here, and simply apply three settings:

- first I will light up the image as much as possible:

 

 

We can now see what appears to be coherent data where there was previously nothing.

 

- then I will apply an Auto Enhance command (basically a set of options with various combinations of light/contrast/sharpness/colour balance, whatever: I chose one) and then Scratch Removal, which is essentially a coordinated blurring tool, on the segment of the open window:

 

 

 

And here, I have added a few indications to facilitate the analysis:

 

 

 

So here, with the Dillard Picture, we find a second type of forgery: the total blacking out of unwanted data. We have already seen this in the "Assassins' Team Behind the Fence", with the complete darkness over the retaining wall and fence, and we will another striking example in Moorman.

Here again, we have indisputable evidence of Federal treachery and felony.

The results presented just above, anyhow, confirms how efficient and easy the process is: the results are simply three-steps-removed from the processed result used as a source...

I will continue with this in a day or two..

[Christian Toussay]

1 hour ago, Richard Bertolino said:

I still don't understand how you got the police officer from the original. I guess I'm just too stupid.

 

...I don't think so, if you were you wouldn't be here I presume.

As explained, I will end this presentation with a specific thread on the scientific basis of what I am doing, and presenting here.

I had tried to explain as simply as possible how this is done. There are no more than three operational steps: choose a source; derivate; interpolate.

The retrieval of the DPD image is possible simply because it is present in the data set under analysis, even though invisible to human eyes.

That is the actual definition of "weak signals"....

 

I will show how the conceptual fame of this apparently uncanny process I developed has been now validated by experts, and validated in peer reviewed scientific paper.

 

So, on to tomorrow for more evidence of the forgery...

 

 

Edited April 28 by Christian Toussay

[Richard Bertolino]

,

Edited May 16 by Richard Bertolino

[Bill Fite]

Hi Christian

I've wondered about a process to do what you are doing since seeing Tom Wilson's interview.

Would the process that you are doing consist of these steps?

• The image we see is a blending of adjacent pixel values of different wavelengths of light on the black - grey - white scale for example.
• Estimating the primary component  wavelength or a confounding component wavelength. 
• Removing that component
• Viewing resulting image to assess results

Repeat process to remove another candidate component's wavelength.

(With some pixel by pixel randomness added?)

Or is that off base? 

[Christian Toussay]

13 hours ago, Richard Bertolino said:

I don't see how it is even theoretically possible to do what is being claimed here. If the original Powell being used is from an online digitization, then the resolution is going to be relatively low. And the photographic information is going to be limited to the pixel resolution, each pixel being an approximate average of original analog photographic information. If there really was information reflecting a hidden police officer in the window in the original analog photographic fake, then it would be lost in the digitization process. And, as the original Powell slide has never been available, the only versions available online are digitizations of prints from the slide made by the government, which would cause the loss of even more of the original photographic information. And even those "orignal" prints are not available. I don't think this analysis is even theoretically possible unless you have the original analog source material.

 

I appreciate that you express your skepticism with courtesy.

First thing I'd like to ask is: have you tried the process yourself to see what it is about ? I have explained several times, including here, the very basic and limited operational steps (3...) to do it, if you are interested, and then we can talk about it if you want.

Secondly, you state that " If there really was information reflecting a hidden police officer in the window in the original analog photographic fake, then it would be lost in the digitization process."

Now how can you be so certain of that, since the process I am trying to present here has absolutely nothing to do with conventional image processing techniques?  I will show you, as an example, how this simple methodology was able to beat the HSCA experts of 1978 when we will analyze the BlackDogMan artifacts in this thread.

I have already mentioned, in a previous post here, that the last thread of this presentation will be specifically dedicated to the science behind the results here.

I also said that, when I checked scientific papers in 1998/2000, I could not find anything comparable to what I was doing, but, that in 2014, I did.

So, how about some homework 😉 and then we'll discuss it? 

If you can't find anything, let me know and I'll give you a clue...

 

[Michael Crane]

23 hours ago, Christian Toussay said:

 

Ok, the link prblm is apparently solved.

I will update all preceding threads with those new links.

 

OK, so we've seen that, just as the Ruler's Puzzle in the back-of-the-head autopsy picture, the Powell / Dillard box discrepancy is explained by forgery of the record: in the first case, it was about suppressing the occipital exit wound; in the second case, it was about suppressing the presence of a man in DPD uniform in the Sniper's Nest, about 30 seconds after the last shot.

In both case, Special FX, i.e. the inclusion in the data set of deceptive information was used: fake wet hair to hide the occipital wound, and a stack of box to hide the DPD officer.

That's one method, that we will find again in the Zapruder and Nix films.

But let us see different technique of the forgers. I am reposting below (not sure it is still accessible here) the Dillard picture:

 

 

As captioned, this is an FBI document, so the black arrow pointing at nothing intrigued me. So I decided to also processed, just in case, the Dillard picture.

 

I post below a result from that processing:

 

 

And here are two different iterations from the data bank:

 

 

 

 

So this is the fourth picture, so far, being presented here of a man wearing a DPD uniform present in the Sniper's Nest from 10 minutes before (Bronson film) to 30 seconds after (Dillard / Powell) the shooting, all this data coming from different material, different point of view and different time sequences.

That's quite a lot of corroborative data.

But the discovery of this man does not actually resolve the mystery of the FBI Arrow.

As I am about to post, I realize I can't locate the files I wanted to present about the solution to this Arrow problem....

So this is what I'll do; I will use the processed result posted here, and simply apply three settings:

- first I will light up the image as much as possible:

 

 

We can now see what appears to be coherent data where there was previously nothing.

 

- then I will apply an Auto Enhance command (basically a set of options with various combinations of light/contrast/sharpness/colour balance, whatever: I chose one) and then Scratch Removal, which is essentially a coordinated blurring tool, on the segment of the open window:

 

 

 

And here, I have added a few indications to facilitate the analysis:

 

 

 

So here, with the Dillard Picture, we find a second type of forgery: the total blacking out of unwanted data. We have already seen this in the "Assassins' Team Behind the Fence", with the complete darkness over the retaining wall and fence, and we will another striking example in Moorman.

Here again, we have indisputable evidence of Federal treachery and felony.

The results presented just above, anyhow, confirms how efficient and easy the process is: the results are simply three-steps-removed from the processed result used as a source...

I will continue with this in a day or two..

Hey,

I went to High School with that guy.

[Christian Toussay]

11 hours ago, Bill Fite said:

Hi Christian

I've wondered about a process to do what you are doing since seeing Tom Wilson's interview.

Would the process that you are doing consist of these steps?

• The image we see is a blending of adjacent pixel values of different wavelengths of light on the black - grey - white scale for example.
• Estimating the primary component  wavelength or a confounding component wavelength. 
• Removing that component
• Viewing resulting image to assess results

Repeat process to remove another candidate component's wavelength.

(With some pixel by pixel randomness added?)

Or is that off base? 

 

..Hi Bill,

Glad to see you're keeping an eye on this....

As I explained, I have no formal scientific training: the concept was designed as a thought experiment about retrieving weak signals in finite data sets in market research. So I only applied it to pictures when I realized that they were de facto finite data sets, and the theorical process should be operational, if it worked, on pictures also.

Basically, the process rests on the generations of N derivations of the source set, which are cross checked against each other in a theorically endless feedback loop.

So yes, the images presented (results) are always a blending of N iterations, themselves generated by the interpolation of N previous iterations.

And there is an averaging, along the process, of the value of the different groups of pixels forming the image.

So what would seem to be about, in my opinion, is that the process is a mix of a Bayesan approach (the new derivations from the source constituting the required "new objective information") and Frequency, with the more resilient values prevailing along the course other the rest, while the feedback loop crunches/cross checks the ever increasing data bank against itself.

Actually, when I designed this, I thought it was actually quite simplistic.

Again, the process does not require any sophisticated knowledge in programming or image processing. I would not know how to remove a specific layer from a picture, as Tom Wilson did. I simply use the overlay tool to interpolate two different iterations, and assess the results. I of course use the usual image processing tools, like light, contrast, sharpness, softening, etc. at will on any iteration.

That's all.

I would be, I think, out of my depth, in trying to go further than that in terms of scientific language.

I realized long ago, after the first undeniable results I was obtaining, that this would have to be litterally back engineered by someone capable of explaining it in acceptable scientific language. This I can't do.

If you want to pursue this, I can supply you with a complete file on some specific picture, so that you can analyze the data bank from source to final result, and verify how the image appears incrementally.

[Pat Speer]

On 4/26/2024 at 12:45 AM, Richard Bertolino said:

The differences between the box positions between the Dillard and "Powell" photos can be explained by the difference in camera perspective. The same 3-dimensional box positions can look different in two dimensional photographs taken from different positions. Comparing to photos taken a few minutes later, the boxes do seem to have been moved, but the Powell and Dillard seem to be consistent.