Abstract
A flexible representation of quantum images (FRQI) was proposed to facilitate the extension of classical (non-quantum)-like image processing applications to the quantum computing domain. The representation encodes a quantum image in the form of a normalized state, which captures information about colors and their corresponding positions in the images. Since its conception, a handful of processing transformations have been formulated, among which are the geometric transformations on quantum images (GTQI) and the CTQI that are focused on the color information of the images. In addition, extensions and applications of FRQI representation, such as multi-channel representation for quantum images (MCQI), quantum image data searching, watermarking strategies for quantum images, a framework to produce movies on quantum computers and a blueprint for quantum video encryption and decryption have also been suggested. These proposals extend classical-like image and video processing applications to the quantum computing domain and offer a significant speed-up with low computational resources in comparison to performing the same tasks on traditional computing devices. Each of the algorithms and the mathematical foundations for their execution were simulated using classical computing resources, and their results were analyzed alongside other classical computing equivalents. The work presented in this review is intended to serve as the epitome of advances made in FRQI quantum image processing over the past five years and to simulate further interest geared towards the realization of some secure and efficient image and video processing applications on quantum computers.
Highlights
Computer science and information systems are disciplines that have penetrated into every aspect of human activities
The geometric transformations on quantum images (GTQI) transformations reviewed in the preceding subsection were focused solely on the spatial content encoded in the flexible representation of quantum images (FRQI) quantum image
An multi-channel representation for quantum images (MCQI) quantum image is stored in the preparation process using the MC-preparation theorem (PPT) theorem, and it is retrieved by means of the quantum measurement on each color channel of it [28]
Summary
Computer science and information systems are disciplines that have penetrated into every aspect of human activities. It offers a significant speed-up in comparison to performing the same task on traditional computing devices by transforming multiple images in a strip simultaneously. It is achieved by using low computational resources, which are only a single Hadamard gate combined with m + 1 quantum measurement operations.
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