Quantum methods in image processing based on the use of Hadamar gates for object boundary detection

Abstract

In this study, both traditional and quantum image processing methods are considered in order to highlight the boundaries of objects. For efficient encoding and processing of pixel intensities, the use of quantum ventilation, in particular the Hadamard transform, is being studied. Quantum algorithms can work with exponential acceleration compared to classical methods; this is especially important for working with large images. The study examines the influence of quantum transformations on the boundary determination process, as well as methods of amplitude permutations to obtain data on edge elements. The superposition and entanglement of qubits have shown to improve the performance and accuracy of the algorithm when processing multiple boundaries simultaneously. It has now been established that quantum computation of intensity differences between neighboring pixels plays an important role in boundary detection. Experiments with 64x64 pixel images have shown that the quantum algorithm performs well in image processing tasks. It has been substantiated that the use of the quantum approach increases processing speed and reduces computational costs. A quantum circuit of the algorithm with its main transformation stages is presented. In general, pathways for further optimization of the algorithm have been developed, which include reducing the number of qubits and adapting it for more complex images.