Development and Research of Quantum Models for Image Conversion

Quantum imaging is a new trend that is showing promising results as a powerful addition to the arsenal of imaging techniques. Per-pixel representation of an image using classical information requires a huge amount of computational resources. Hence, exploring techniques for representing images in a different information paradigm is important. This paper describes the variety of options for representing images in quantum information. Image processing is a well-established area of computer sciencewith many applications in today'sworld such as face recognition, image analysis, image segmentation and noise reduction using a wide range of techniques. A promising first step was the exponentially efficient implementation of the Fourier transform in quantum computers versus the FFT in classical computers. In addition, images encoded in quantum information can obey unique quantum properties such as superposition or entanglement. The laws of quantum mechanics can reduce the required resources for some tasks by many orders of magnitude if the image data is encoded in the quantum state of a suitable physical system. The aim of this work is to develop and study quantum models of image transformation.