Visual ITC can be encountered in many different ways. The common denominator is the availability of chaotic light somewhere in the field of view of a camera. For instance, the video feedback loop is used as a chaotic light generator. As you will see below, light reflected from many different surfaces is also chaotic, and when closely examined in photographs, may support phenomenal images.
This example was collected by Arthur Soesman using what is sometimes referred to as the Arthur Soesman method. It is illustrated in the accompanying picture (right). In this technique, the bottle is partially filled with liquid and then agitated while a picture is taken of the surface of the water.
In the picture at the left, you can see the face of a man inside of the red square.
Thanks for this very valuable article. It really makes me rethinking my experience with ITC pictures. In all techniques i tried and read from, there always was movement a part of the process of gaining spirit images. All setups that are using reflections in water always used water in movement and the video feedback loop uses the movement o the self-oscillation. But here we have static conditions, nothing moves. Seems to me that the movement in time is replaced by a spatial movement represented by the ‘noisy’ structure of the tv screen. Would be interesting to know if the taken spirit image also was constant or just appeared while the shot was done.
I think the question is still open concerning if the features are really moving pictures or snapshots. There are examples of a feature forming and then dissipating over a series of consecutive frames, the feature is static. It is the technology that makes it seem moving … the limits of our equipment.
We mostly see two kinds of features. One is the snapshot that did not exist in the sample before or after. It may be forming, but the evident intended order is a snapshot.
The second it the feature that is always there. An example is the famous Jesus on burnt toast. The majority of such reports are probably accidents f nature, but a few make us wonder.
I have drafted a Best Practices titled Classifying Phenomena It is at https://atransc.org/classifying-phenomena/. In it, you will see that I classify permanent features as Type 2: Always present; often as a persistent artifact.