Synthetic Surfaces

Investigating the visual representation of artificially constructed surfaces, characterized by the utilization of randomly generated values.

All digital images are a product of encoding, a process that transforms seemingly complex organic wholes into a vast collection of exceedingly simple elements. Within the digital landscape, images are ‘atomized’ and broken down into basic constituent parts. These constituents are guided by calculations rooted in the algorithmic and coded structure of their surfaces.

The JPEG algorithm, designed specifically to compress photographic images, illustrates this process with a clear mathematical structure. It operates on a range of constants with values that extend from 0 to 255. This seemingly rudimentary range belies the complexity of the digital image. The question arises: what transformative results could be produced by decoding the JPEG structure and then reconstructing it using randomly generated values?

To explore this notion, a conceptual experiment was devised wherein ‘live’ random RGB values (255,255,255) were generated on one screen. These values were then utilized to construct a ‘live’ JPEG on a second screen. However, this newly built JPEG was devoid of any conventional representational form. The experiment was facilitated through Python programming, and the resulting code was run on a computer connected to two monitors via HDMI. Within the code, control over the ‘pixel blocks’ size allowed for flexibility in visual output. Creating a full HD screen (1920 x 1080) filled with randomized colored pixels took over two hours, leading to adjustments in pixel size to achieve a more satisfying result.

The intriguing aspect of this endeavor lay in the vast amount of data required to generate a single full HD frame in color. It offers a profound insight into the daily consumption of data in our digitized lives, shedding light on the underlying complexity of seemingly simple digital interactions.

The resulting images, which were synthetic and constructed purely through mathematical computations, were devoid of any traditional representation. These abstract visuals could be seen as algorithmic fractals and might be interpreted as a form of counter-information resistance. Through this lens, the experiment uncovers an intricate dance between the organic and computational, between representation and abstraction. It offers a critical reflection on the nature of digital imagery, calling into question traditional understandings of form and content, while providing a unique window into the underlying mechanics of digital creation.

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