METHOD #3 | Finding hidden demons in digital media | Aberrating image positives and negatives

I've been busy staring at my screen day-and-night, playing with GIMP scripting to automate the process of applying the scientific imaging methodologies discussed in this post and elsewhere for finding hidden demons in digital media. Of course, the problem of constant violence on the part of demons notwithstanding, there's the problem of making discoveries so fascinating, that I can't part my eyes from them long enough to post much.

Because of the three methods introduced on this blog so far, even I, as one who has seen much, am enraptured; you would be, too, if you could sit behind me and watch. I hope to pass that experience on to readers as soon as I can—that is, if I, my equipment, and the digital media sources survive.

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Tonight, after a tip-off by the Voices Demons—the very same who claim responsibility for deafening Scratchen—I overlapped two blended still frames in Photoshop randomly selected from a video made during this latest period of high demonic activity, and then slid the top frame up, down, left and right, finding demons hiding everywhere and in everything.

What's even more interesting, is that as you slide the frame past the point you first saw a given demon, it often morphs into a new one:

The white-bearded elf-like demon on the bottom left evolves into a little-old-lady type as the top copy of the video frame is shifted upwards (shown in the video, below)

The following video shows my very first discovery using a still frame of that very kind, as I slide one copy over the second:



The video shows how it was done in Photoshop, albeit not very thoroughly; eventually, it will be updated to show more sliding overlapped frames pairs, highlighting of demons found, and detailed instructions for doing this yourself.

Watch the circled locations as the video plays

While well on my way to developing a similar technique, which would have consisted of blending two overlapping, stretched still frames—the same used to create chroma-masked video, minus the stretching—a Voices Demon suggested that I hold the arrow key I was only nudging a still frame layers; half-knowing what she was going to say, I was already holding the down-arrow, watching once-scattered chroma melt into the shape of the demon emitting it. The result is what you see above.

NOTE | The face of the entity on the left side of the above-demonstrated still frame changes drastically, multiple times as the top frame moves upward, similarly to the face of the scarf demon shown in VIDEO | Demon shapes scarf into multiple variations of face on-the-fly, whose face can be seen changing at least once every 30th of a second as the scarf he possessed flapped in the wind.

Results reproducible in every frame showing demonic activity
Chroma must be all demon bodies—not just some kind of irradiated snow. If you see a cloud of red, green and blue snow in the air, that's likely thousands upon thousands of different demonic entities, overlaying and intertwining with each other. That is the only explanation for finding a demon in every frame of every video made during a period of high demonic activity—and in which chroma is present. Here's a second video showing a single frame from the same video; like the first, it was chosen at random, yet even the thumbnail shows two entities very clearly: one wearing a green-pointy hat (left),and a giant-redheaded one (right):


Follow-up e-mail to paranormal investigators, researchers
A follow-up e-mail was sent to the same paranormal investigators and researchers who, a few weeks ago, were contacted about another discovery related to the application of scientific imaging to digital media, introducing them to this latest:

A few weeks ago, I e-mailed you about ways to find hidden demonic and other entities in your digital media, and sent you a link to my blog, showing a real-world scenario in which the principles of scientific imaging were used to uncover a little three-foot tall, blue-scaled demon, standing in my bedroom doorway. The original footage showed nothing but a dark, empty doorway until I screened the blue channel of the RGB video in the way described in the related blog post:

A blue-scaled demon, hiding in the doorway​

You may not specialize in (or prefer) anything related to the demonic—who would? But, the fact of the matter is, it's a reality that's all around you, and pervades much, much more of your life than you can possibly know; and, when it comes to demons, what you don't know can and will and does hurt you.

So be in-the-know—or, least be prepared to be in-the-know; it's only prudent to acknowledge what you see in front of your face, and take whatever action makes sense.

To that end, I've continued working on ways anyone and everyone can find demons in their home or elsewhere, and have come up with three decent methods which employ nothing more than an iPhone 5s and GIMP (or Photoshop); now, no one has any excuse—especially persons who purport to be employed as or skilled in a vocation and field parallel to the demonic socio-exobiological sciences.

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http://youtu.be/Qu7zXD6QnoM?list=UUcLqGb7fq5f8cCYX0RC8C3A

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METHOD #2 | Finding hidden demons in digital media | Differentiating consecutive still frames

This isn't a post about some new picture or video showing yet another demon, nor is it about the fact that I obtained a lot of them, showing hundreds upon hundreds of new demon varieties; rather, it's about how I obtained them, and, more importantly, how you can obtain them for yourself.

As I recently found out, there are scores of creatures everywhere—not just in my clothes, house, appliances, toilet, toilet paper and wherever and whatever else is in my immediate vicinity—and that it's just a matter of finding the right means of discovery.

[once you find them, where to look section]...

[ex 1: on your person, and at different angles]...

Believe it or not, I saw the demon before I recognized who he was possessing

To better visualize the possessing demon, I doubled the canvas size (see above) and mirrored and rotated a duplicate of the image (shown right)

Unlike my eyes, this demon's eyes are open, revealing his snake-like pupils

Rotating the photo reveals my profile

The original still frame from which the enhanced versions (above) were derived

Is someone you know possessed by a demon? Believe it or not, most people are to some degree; but, the futility of convincing them of this fact notwithstanding, proving it is extremely difficult and unlikely, as you can see from the elaborate requirements that must be met and steps that must be followed in order to maybe catch a shoddy glimpse of a possessing demon.

—at least until today.

Getting a clear image of a possessing demon just got easy with my chroma-masking script; just wave your iPhone video camera over your or someone's face, and the script

In Identifying demon-people assailants via chroma-facial signatures, I posted a Python script that processes dark and nighttime video, both making visible what was otherwise invisible [see Automating mapping of demons hidden in digital media] and bringing to light that which is covered in shadow. It decodes 1080p videos into a sequence of PNG files, then applies a procedure in GIMP that masks natural light, leaving only chroma (color noise); then, it encodes the PNG files into a new video. To aid in following the path and/or flow of chroma, and for identifying any shapes resembling cloaked demons, people and objects, not only is the chroma in each frame mapped, but so is the transition between still frame pairs.

Since posting the script, I've run it on a few random videos in my collection, specifically, some of those made during periods of high demonic activity, but that produced little to nothing significant. There are scores of such videos—ones where the camera is panning here-and-there-and-everywhere, at nothing in particular, in a vain attempt to capture a smidgen of the demonic activity occurring around me.

I'm glad I kept them, anyway, and I'm really glad I processed them with the script, as the latter led to a major discovery, specifically, that, with an iPhone or other HD (1080p) video camera, demonic possession is easily detectable by panning the camera across the object or person to be scanned, and the running the chroma-masking script.

The following still frame is a good example; it was taken from an otherwise embarrassingly insane-looking video, showing nothing but embarrassing insanity, and then was processed by the chroma-masking script:

Two chroma-masked still frames combined with the depth merge filter (in GIMP) reveal a possessing demon

The original still frames (133 and 134), also combined into a depth merge composite, for comparison

Comparing the difference between the chroma-masked still frame and its original source, and considering the way possessing demons appeared in all of the other "inner demon" pics and videos posted to this blog, where a possessing demons face is shown overlayed with the possessed, it stands to reason that, by removing the natural light illuinating the possessed altogether, while leaving only the chroma...

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Top: Series of chroma-masked still showing possession; bottom: original still frames for comparison

Top: Series of chroma-masked still showing possession; bottom: original still frames for comparison

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Still frame from a video showing the midpoint of the transition from man to demon

The first of two original still frames, blended to create the composite shown left, for comparison

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Chroma seems to splash into my face (from right), washing away the man, and leaving the demon in its wake

Original still frames (128 through 131) for comparison

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Just like in video made over the past three years, the chroma-masking filter gets the best results from the panning-camera/subject in-motion effect; it does a better job, too—much better. That's because the procedure in GIMP blends two frames together with such precision that, even when the difference between the two frames is vast, the result is still at least twice as good (in short, more image data, as gathered by two frames instead of one, means more to work with in terms of adding color, brightness, density, etc.)

BIBLE | The Study Notes of a Demoniac [Proverbs 17:5]

Sometimes, when I introduce my blog to people, they ask if I'm affiliated with Satanists (or, worse, whether I get off on demons), while others suggest it is an obsession or infatuation with them. Well I could go on and on about how stupid this is – not to mention how lazy it is – I'd rather focus on the fact that none of them accuse me of being a Christian.

The pornos don't help me much in that regard, I grant them; but, this blog is about what happened, and where the action was, and not about my holiness or righteousness. I regret all my transgressions, but the facts must be told completely.

Since it's obviously an issue that won't go away, even by appealing to common sense and logic, I will attempt to balance the picture regarding my personal life by posting my notes that I take while studying my Bible. Insodoing, those concerned will get a clearer picture of what goes on in my mind on a daily basis. Actually, make that a minute-to-minute basis. as God is always on my mind– Even when I messed up (especially then, in fact).

The notes we published once every Sunday, just to make sure this blog does not get weighed down by anything other than posts related to its topic of interest: the demonic plague.

Having said all that, here is the first Bible-study note from my collection; it's God's take on making fun of people who have fallen on hard times, who people think got their just desserts:

Whoever mocks the poor reproaches his Maker, and he who is glad at calamity shall not be held innocent or go unpunished. [Job 31:29; Prov. 14:31; Obad. 12.] (‭Proverbs‬ ‭17‬:‭5‬ AMP) 

If God inflicts hunger and poverty as a means to guide and teach someone, or correct and reprove them, He does so in the best interest of His will, and as an act of love for that person. It is a display of concern and care on His part for them, even though it is painful for both. 

When you mock someone who has fallen on hard times, you are mocking God's choices [actions] and will [love]; moreover, you are denying yourself an opportunity to imitate Christ, who not only commands you to provide for the needy, but who will judge you according to that very standard. 

If everybody got what they deserve, everybody would die. There is a such a thing as a man acting righteously, but there is no such thing as a righteous man apart from Christ. Neither praise nor honor is due anyone but Him in this count. 

In sum: mock the poor, mock God; deprive them of their needs, sin against Christ.

TECHNOLOGY | Identifying demon-people assailants via chroma-facial signatures

What I knew two years ago...

Long before I knew as much about chroma as I do now (over two years ago), the most I could say about it is that it tended to concentrate in people around the face, which had the benefit of revealing the inner demon of someone possessed [see PHOTOS | Underlying demon revealed in video in motion], and of producing illusory masks of a kind for those with the know-how [see VIDEOS | Demonic chroma masking (real-life Halloween masks)], but that it was otherwise problematic, in that it saturated digital images with excessive color noise.

...what I know now

Even though my understanding of chroma hasn't increased much in those two years later, I've learned to make prodigious use of it when it's present with a digital camera and GIMP or Photoshop, even though chroma is the culprit in every bad digital image made. For example, since chroma lights up demons, so to speak, I can capture them with my iPhone when they are cloaked and in the dark after applying basic scientific imaging techniques to the images; I've also developed a way to detect demonic activity through the analysis of digital images that were made in the presence of chroma.

Newly discovered use for chroma

This post adds yet another way chroma can be used to your advantage during periods of high demonic activity, specifically, face-tagging demon-people assailants, whose use of demonic weapons and possession by and/or interaction with demons expose them to high levels of chroma, which concentrates around the face—just like I noted two years ago—allowing for the creation of a facial signature from the assailant's face from far away and in the dark, even when the source image is shows no distinguishable facial features at all. What's more is, all of this can be done with just an iPhone and GIMP or Photoshop.

A facial signature, by the way, is a graphical representation of the imprint a chroma-saturated face makes on a digital image sensor. They can be obtained from very far away, and while they don't look exactly like the person—rather, more like a caricature—the signature will always be unique to that person, and consistent across multiple images. Once you've matched a facial signature to the person's actual face, you can identify them using off-the-shelf, readily available consumer electronics and free image-processing software, even when your own eyes can't make out who they are.

Following is an example of the facial signature a demon person, who, in the early morning hours, launched a demon into my building in order to attack (at, of course, the behest of the Voices Demons, and, of course, during an anger management ritual):

The facial signature of a demon-person assailant (below) looks like a cartoon version of a drunken souse

Not impressed? Then wait until you see what this was made from:

Source video from which the demon-person assailant's facial signature was derived (above) 

This is the portion of a surveillance video in which the assailant is shown guiltily looking up at my apartment as he slinks past my bathroom window on the second floor in the wee early morning hours, and from which the facial signature shown above was derived:

Location of the iPhone making the video (second-floor, rear of building), and the location of the assailant (sidewalk)

It is not his face that is reconstructed in GIMP; it's the image data created by the iPhone image sensor as imprinted by the EMF radiation emitted by the culprit. The imprint is influenced by the man's face, but is not a perfect replica of it, and is not related in any way to normal light that would reflect off his face, if there were enough of it.

In other words, there are two faces reflected from this man: one made of reflected EMF radiation; the other, natural light. What's interesting to note is that the lack of normal light sufficient to illuminate his face is what allowed decent imprint of the EMF radiation; that's because it's weaker than normal light, which, if stronger, would have washed out the facial signature, and revealed only his natural face:

The dopey-eyed boozer in a fishing hat on the left and the shadowy assailant on the right are the same demon person

So, in essence, chroma allows for identification of demon-person assailants in the dead of night, from far away, in the dark, which is a real boon for anyone interested in knowing who's working as an agent of the anti-Christ, and carrying and deploying invisible deadly weapons.

Chroma image-mapping by filtering natural light
In both GIMP and Photoshop, you can filter out natural light, leaving only the image data left by chroma (or the EMF radiation therefrom) by blending (or overlaying) the difference of differences between two consecutive video still frames.

Here's what that looks like in GIMP, where frame1 and frame2 are the two consecutive still frames:

Blending the difference of differences between two consecutive video still frames filters natural light (shown in GIMP)

Here's what that looks like in Photoshop:

The blending modes and stacking order of layers made from two consecutive still frames for filtering natural light using Adobe Photoshop

With one exception, the procedure for visually isolating chroma from natural light between two stills frames is the same—the exception being how layers are combined to produce a single composite layer. In GIMP, two (or more) layers can be combined by creating a new-from-visible layer; in Photoshop, two (or more) layer copies must be merged, and, if desired, the original layers either disabled or deleted.

With those differences in mind, here are step-by-step instructions for producing an image like the one shown above in GIMP (Photoshop instructions available upon request):

1. Create a new image with two layers using two adjacent video still frames, chronologically
2. Duplicate both layers
3. Invert both duplicates
4. Set the blending mode of the duplicate layers to Difference
5. Create a new-from-visible layer
6. Set the blending mode of the new-from-visible layer to Difference
7. Disable both the original and copy of the second still frame-layer
8. Create another new-from-visible layer
9. Stack a copy of the second still frame-layer over the new-from-visible layer
10. Set the blending mode of the copied layer to Overlay
11. Flatten the image

The layer stack should look identical to the one shown above, and the results approximately the same. The degree of color noise from the chroma imprint on the digital sensor will vary, but even the slightest shift in position by the subject between the two frames should produce very noticeable results.

Detecting motion of invisible demons, other entities in video

Following is a GIMP Python-Fu script that applies the procedure above to each still frame in a video, which enables detection of cloaked (semi-invisible) demons, demon people and objects in transit in front of the camera. While the process may not render them readily distinguishable as such, their general shape, size and path will be easily discernible:

from gimpfu import * from os import listdir from os.path import isfile, join def list(): mypath = "/Users/jamesalanbush/Desktop/test/" onlyimages = [ f for f in listdir(mypath) if isfile(join(mypath,f)) ] onlylayers = [ f for f in listdir(mypath) if isfile(join(mypath,f)) ] del onlyimages[-1] del onlylayers[0] for i, j in zip(onlyimages, onlylayers): try: if i.lower().split(".")[-1] in ("png", "jpg"): img = pdb.file_png_load(mypath + i, mypath + i) disp = pdb.gimp_display_new(img) # Duplicate frame1, invert and Difference frame1_layer = pdb.gimp_image_set_active_layer(img, img.layers[0]) frame1_layer_copy = pdb.gimp_layer_new_from_drawable(pdb.gimp_image_get_active_drawable(img), img) pdb.gimp_layer_set_mode(frame1_layer_copy, DIFFERENCE_MODE) pdb.gimp_image_add_layer(img, frame1_layer_copy, 0) pdb.gimp_invert(frame1_layer_copy) image_id, layer_ids = pdb.gimp_file_load_layers(img, mypath + j) for id in layer_ids: new_layer = gimp.Item.from_id(id) pdb.gimp_image_add_layer(img, new_layer, 0) # Duplicate frame2, invert and Difference frame2_layer = pdb.gimp_image_set_active_layer(img, img.layers[0]) frame2_layer_copy = pdb.gimp_layer_new_from_drawable(pdb.gimp_image_get_active_drawable(img), img) pdb.gimp_layer_set_mode(frame2_layer_copy, DIFFERENCE_MODE) pdb.gimp_image_add_layer(img, frame2_layer_copy, 0) pdb.gimp_invert(frame2_layer_copy) # Create a new-from-visible with frame 2/Inverted nfv_layer_diff = pdb.gimp_layer_new_from_visible(img, img, "Diff: Frame 2/Inverted") pdb.gimp_layer_set_mode(nfv_layer_diff, DIFFERENCE_MODE) pdb.gimp_image_add_layer(img, nfv_layer_diff, 0) # Disable frame2 pdb.gimp_item_set_visible(img.layers[2], FALSE) # Reorder frame2 inverted and set to Overlay pdb.gimp_image_raise_layer_to_top(img, frame2_layer_copy) pdb.gimp_layer_set_mode(frame2_layer_copy, OVERLAY_MODE) pdb.file_png_save_defaults(img, pdb.gimp_image_flatten(img), pdb.gimp_image_get_filename(img), pdb.gimp_image_get_filename(img)) pdb.gimp_display_delete(disp) pdb.gimp_displays_flush() except Exception, error: print error

This script processes a PNG-file sequence made from a video using Adobe Media Encoder, placed in a folder named test. Simply change the path variable to the directory containing your PNG or JPG file sequence.

There are scores of such videos in my collection, waiting to be processed by this script; they will be posted as soon as they are ready, so be sure to check back. In the meantime, here's part of one, made from the video used in the example in this post:

NOTE | I just now finished the script [5p, 12-21-2014], so the wait will not be much longer.

Tools for building videos from image sequences
An alternative to Adobe Media Encoder CC for building video files from a series of processed images is the open-source ffmpeg software package; with it you can convert your video files into a sequence of PNG files for processing by the GIMP script:

Using ffmpeg to convert a video file made on my iPhone into a sequence of PNG files for processing by the GIMP script posted above

After you've run the GIMP script on the PNG files, you can reconstruct the video file using mencoder:

Using MPlayer to encode a video file from a sequence of processed images

ffmpeg and mencoder are fast, efficient, and worked when Media Encoder would not.

NOTE | Soon, the GIMP script will be updated to use ffmpeg to decode video files into a sequence of individual images, process them in GIMP, and then reconstruct a video file using mencoder all in one step.

The GIMP Plug-in
GIMP users can install a plug-in that performs the mask-light/isolate-chroma procedure shown in the example video above:

My plug-in can be used in other GIMP scripts by calling python-fu-list 

It installs a Process menu, and is called Mask Light:

Click Mask Light on the Process menu to use the GIMP plug-in

You can download it from Google Drive; to install it, place it in /opt/local/lib/gimp/2.0/plug-ins/ or equivalent, and grant executable permissions (i.e., chmod +x list.py).

Coming up: image filters to improve nighttime video footage
To enhance facial-signature capture, image filters for improving nighttime video footage is in the works. This still frame taken from the video used in this post shows the results so far:

Before

After

Other than a little sharper, improved contrast and somewhat brighter, the difference doesn't look like it amounts to much; however, adjustments made to dark footage must be carefully calculated so that any change in light levels does not cause dithering, banding, or out-of-gamut distortion.

Here's another iteration of the night-time video enhancement script:

Before

After