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Given a function from low-light to normal-light images, is it injective? That is, does more than one input produce the same output? If so, how many? And more pr
by hyperpallium 8y ago
Given a function from low-light to normal-light images, is it injective? That is, does more than one input produce the same output? If so, how many? And more practically, how different are they? Is it semantically injective?
One feature seems that low-level granular noise is smoothed away. One can imagine many instances of noise that would be appropriately represented by a smooth gradient. But there are also noisy patterns that average out to a gradient, that shouldn't be represented by a gradient, because they form some other pattern.
Unfortunately, an objective, rigourous measure of whether this system is semantically injective or not wpuld require a formal model of image interpretation... pretty much strong AI.
- joshvm 8y agoYes, it's a many-to-one. Ignoring optical aberrations and losses from the lens, there's always additive noise that does not depend on the number of photons incident on the sensor. That could be dark/thermal noise, noise in the readout electronics, noise coupled in from external RF sources, etc. You could expose the detector with exactly the same number of photons 1000 times and get 1000 different images.