Relativistic Image Transformer

Simulates what a printed picture would look like when approached at near-light speed.

Original	v = 0.7 c

Effects

• Relativistic aberration -- image compressed into a forward cone
• Relativistic Doppler shift -- spectral color change via Gaussian basis reconstruction
• Searchlight effect -- D^5 brightness scaling (center bright, edges dark)
• Spectral redistribution -- UV/IR crossover (visible light shifts to UV, IR shifts into visible)

Usage

python relativistic_transform.py img.jpg                          # defaults: beta=0.5, FOV=60
python relativistic_transform.py img.jpg -b 0.9 --debug           # high speed + debug plots
python relativistic_transform.py img.jpg -b 0.3 -o out.png        # moderate speed
python relativistic_transform.py img.jpg -b 0.99 --tone-map log   # extreme speed

Arguments

Argument	Default	Description
input	(required)	Path to input image
-o, --output	auto	Output path (<stem>_relativistic.png)
-b, --beta	0.5	Velocity as fraction of c, in [0, 1)
--fov	60.0	Horizontal field of view in degrees
--exposure	auto	Manual exposure value
--tone-map	reinhard	Tone mapping: reinhard, log, clamp
--debug	off	Show matplotlib debug visualisation

Dependencies

NumPy, SciPy, Pillow. Optional: Matplotlib (for --debug).

Known Limitations

• Doppler factor range: The precomputed spectral colour matrices cover D values from 0.05 to 30.0. At extreme velocities (beta > ~0.998), the centre Doppler factor exceeds this range and is clamped, which produces incorrect colours. Edge pixels are similarly affected for beta > ~0.99. For reliable results, keep beta below 0.99.