Hype & Spin in Signal &
|The Single Pixel Camera
Does random sampling
achieve better results
than regular under-sampling?
Is the index for the similarity
of two images an improvement
on the noise visibility function?
The citation juggernaut spins
out of control and few researchers
dare suggest that a much simpler
formulation just might be as good,
if not better...
no convincing evidence in this experiment.
Compare with simple under-sampling of images.
citation juggernaut plows on regardless
Google Scholar tracking...
1307 and counting...
|Fallacies: Incites & Insights
defined by the intensity histogram
measures image complexity
|Infinite width of SINC function
rules out its use in accurate interpolation
of discretely sampled band-limited
immune to geometric transformations
can only be embedded in
the transform domains
(i.e. Fourier, DCT, Mellin, and wavelet)
|The human ear is insensitive
to the phase of audio signals
|Pixel value histogram gives no indication
whatsoever of the spatial complexity
or compressibility of a
2-D (or even 1-D)
|Fourier based sinc interpolation is easy
to implement and can actually
Dirichlet sinc is periodic
|Direct spatial domain embedding is
generally easier, faster and
not impossible to
|The evidence for phase sensitivity
is piling up. Digital (DSP) filters
now allow perfect phase and
E.T. Jaynes, 1965
It is clearly meaningless to ask
“What is the entropy of the [system] crystal?"
unless we ﬁrst specify the set of parameters
which define its thermodynamic state.
“Entropy is an anthropomorphic concept"
K.G. Larkin, 2016
Make Shannon Information symmetric in 1D
and everything else follows naturally
into 2D and beyond. Check preprint on arXiv
An example of affine invariant functions
embedded directly in spatial domain (LHS):
Correlation detection survives all affine
distortions (RHS is polar spatial domain ).
Note flashing bright lines are (negligible)
image edge effects.
|Pure Hype & Spin|