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.Entropy 2014, 16 5291The 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.

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Image scrambling is a technique used for confidential storage and transmission as well as for image information hiding. In this study, we propose a multi-channel quantum image scrambling method, which applies both color and geometric transformations of an image. This is a simple and reliable method for transforming a meaningful quantum image into a meaningless or disordered one. We performed two simulation experiments, which demonstrated the efficiency and flexibility of the proposed method. Previous studies mainly developed scrambling strategies for grayscale quantum images, whereas the proposed method is effective for the color image scrambling in the quantum computing domain.