  A quantum Boolean image processing methodology is presented in this work,
with special emphasis in image denoising. A new approach for internal image
representation is outlined together with two new interfaces:
classical-to-quantum and quantum-to-classical. The new quantum-Boolean image
denoising called quantum Boolean mean filter (QBMF) works with computational
basis states (CBS), exclusively. To achieve this, we first decompose the image
into its three color components, i.e., red, green and blue. Then, we get the
bitplanes for each color, e.g., 8 bits-per-pixel, i.e., 8 bitplanes-per-color.
From now on, we will work with the bitplane corresponding to the most
significant bit (MSB) of each color, exclusive manner. After a
classical-to-quantum interface (which includes a classical inverter), we have a
quantum Boolean version of the image within the quantum machine. This
methodology allows us to avoid the problem of quantum measurement, which alters
the results of the measured except in the case of CBS. Said so far is extended
to quantum algorithms outside image processing too. After filtering of the
inverted version of MSB (inside quantum machine) the result passes through a
quantum-classical interface (which involves another classical inverter) and
then proceeds to reassemble each color component and finally the ending
filtered image. Finally, we discuss the more appropriate metrics for image
denoising in a set of experimental results.
