Evaluating the result

Top left: noisy image at 100% zoom. Top right: denoised image at 100%, with grain shaped into quantization error diffusion to retain more detail, even though the image appears to be denoised. Bottom: a 300% zoom of the top right image, revealing the shaped grain.

Given StarTools' general design goal of exploiting psychovisual limitations of the human visual system, there are some important things to take note of when evaluating the result.

Specifically, the module exploits "useful" noise grain (by modelling it as quantization error in the signal) to retain and convey more detail in areas that are too "busy" for the human visual system to notice, without the result appearing noisier. The actual "useful" noise grain, much like dithering, however may be visible when zoomed in at scales beyond 100%.

The value of the module's ability to shape noise grain in this way, becomes particularly apparent when combining this ability with the output of StarTools' deconvolution module. The latter module can be "overdriven" to trade increased detail for increased (though perceptually equalised) fine grain noise "artifacts". The magnitude of the noise grain is subsequently recovered, modeled and shaped for use as quantization error diffusion in the final denoised image.

Of course, if so desired, using more aggressive parameter settings will progressively eliminate such quantization error diffusion, and yield a smooth image.