An RGB Multi-Channel Representation for Images on Quantum Computers

Abstract

RGB multi channel representation is proposed for images on quantum computers (MCQI) that captures information about colors (RGB channels) and their corresponding positions in an image in a normalized quantum state. The proposed representation makes it possible to store the RGB information about an image simultaneously by using 2n+3 qubits for encoding 2n× 2npixel images, whereas pixel-wise processing is necessary in many other quantum image representations, e.g., qubit lattice, grid qubit, and quantum lattice. Simulation of storage and retrieval of MCQI images using human facial images demonstrated that 15 qubits are required for encoding 64 × 64 colored images, and encoded information is retrieved by measurement. Perspectives of designing quantum image operators are also discussed based onMCQI representation, e.g., channel of interest, channel swapping, and restrict version of color transformation.

Quantum image processing: A review of advances in its security technologies

“…Since the FRQI, many other quantum image representations (QIRs) have been proposed as well as an array of algorithmic frameworks that target the spatial or chromatic content of the image. 2 Among others, the multi-channel representation for quantum images (MCQI) 12 and novel enhanced quantum image representation (NEQR) 13 are the representative QIRs that have traced their root to the FRQI representation. In addition, a lot of the e®ort in QIP has been focused on designing algorithms to manipulate the position and color information encoded using the FRQI and its many variants.…”

“…19 Later, MCQI-based channel of interest (CoI) operator to entail shifting the grayscale value of the preselected color channel and the channel swapping (CS) operator to swap the grayscale values between two channels were fully discussed in Ref. 12.…”

“…In addition, MCQI representation provides the potential to design quantum-cryptography-based color image watermarking algorithms. An MCQI image is stored in the preparation process using the multi-channel PPT (MC-PPT) theorem 12 that extends the vector in (FRQI) PPT to three vectors of angles. The computational complexity of the whole preparation for MCQI image is the same as that required for an FRQI image, i.e.…”

A Novel Quantum Image Compression Method Based on JPEG

“…Different quantum image representations may have different preparation methods. Researchers have proposed a number of quantum image representation schemes, such as Qubit Lattice [1], Real Ket [2], Entangled Image [3], FRQI (the flexible representation of quantum images) [4], MCQI (the RGB multi-channel representation for quantum images) [5], NEQR (the novel enhanced quantum representation of digital images) [6], QUALPI (the quantum representation for log-polar images) [7], QSMC&QSNC (quantum states for M colors and quantum states for N coordinates) [8], NAQSS (the normal arbitrary quantum superposition state) [9], INEQR (the improved NEQR) [10], GQIR (the generalized quantum image representation) [11], and etc. A number of papers have summarized and compared them [11][12].…”

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

“…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.…”