A Multi-Channel Representation for images on quantum computers using the RGBα color space

Hybrid Quantum-Classical Protocol for Storage and Retrieval of Discrete-Valued Information

“…Among the theoretical discoveries and promising conjectures that have positioned quantum computation as a key element in modern science, we find: (1) the development of novel and powerful methods of computation that may allow us to significantly increase our processing power for solving certain hard problems [12][13][14][15][17][18][19][20][21][22][23]; (2) the simulation of complex physical systems [5,24,25]; and (3) an increased interest of several applied scientific communities to cross-fertilize their own fields with techniques and ideas from this discipline (e.g., image processing and computational geometry [26][27][28][29][30][31][32][33][34][35][36], pattern recognition [37][38][39][40], quantum games [41], and warfare [42]). A detailed summary of scientific and technological applications of quantum computers can be found in [43,44].…”

Quantum Computation-Based Image Representation, Processing Operations and Their Applications

“…Based on the FRQI representation in Section 2.2, the multi-channel representation for quantum images, MCQI [27,28], was proposed to capture the RGB channel information. This is accomplished by assigning three qubits to encode color information about images.…”

“…are three angles encoding the colors of the R, G and B channels of the i − th pixel, respectively, and θ α is set as zero to make the two coefficients constant (cos θ α = 1 and sin θ α = 0) to carry no information, which is discussed in [27,28].…”

“…A simple example of an MCQI quantum image with its quantum state is shown in Figure 8. The methods for storing and retrieving quantum images are discussed in [27,28,42]. Like FRQI, the MCQI state is also a normalized state, i.e., |I(n) mc = 1, as given by: An MCQI quantum image is stored in the preparation process using the MC-PPT theorem, and it is retrieved by means of the quantum measurement on each color channel of it [28].…”

“…The first steps taken in the area of quantum image processing have involved proposals on representations to capture and store the image on quantum computers. Various representations for images on quantum computers were proposed, such as qubit lattice, wherein the images are two-dimensional arrays of qubits [20], Real Ket, wherein the images are quantum states having gray levels as coefficients of the states [22], grid qubit, in which geometric shapes are encoded in quantum states [23], quantum lattice, wherein color pixels are stored in quantum systems qubit by qubit [24], flexible representation of quantum image (FRQI), wherein the images are normalized states that capture the essential information about every point in an image, i.e., its color and position [21,25,26], and multi-channel quantum image (MCQI) [27,28], which is an extension of FRQI representation that contains the R, G and B channels for processing color information. Among them, FRQI representation is often used and thoroughly studied because it encodes quantum images of the same size using many fewer qubits in comparison with the other methods, and also, it facilitates various classical-like image processing operations.…”