Multi-dimensional color image processing has two difficulties: One is that a large number of bits are needed to store multi-dimensional color images, such as, a three-dimensional color image of $$1024 \times 1024 \times 1024$$ 1024 × 1024 × 1024 needs $$1024 \times 1024 \times 1024 \times 24$$ 1024 × 1024 × 1024 × 24 bits. The other one is that the efficiency or accuracy of image segmentation is not high enough for some images to be used in content-based image search. In order to solve the above problems, this paper proposes a new representation for multi-dimensional color image, called a $$(n\,+\,1)$$ ( n + 1 ) -qubit normal arbitrary quantum superposition state (NAQSS), where $$n$$ n qubits represent colors and coordinates of $${2^n}$$ 2 n pixels (e.g., represent a three-dimensional color image of $$1024 \times 1024 \times 1024$$ 1024 × 1024 × 1024 only using 30 qubits), and the remaining 1 qubit represents an image segmentation information to improve the accuracy of image segmentation. And then we design a general quantum circuit to create the NAQSS state in order to store a multi-dimensional color image in a quantum system and propose a quantum circuit simplification algorithm to reduce the number of the quantum gates of the general quantum circuit. Finally, different strategies to retrieve a whole image or the target sub-image of an image from a quantum system are studied, including Monte Carlo sampling and improved Grover’s algorithm which can search out a coordinate of a target sub-image only running in $$O(\sqrt{N/r} )$$ O ( N / r ) where $$N$$ N and $$r$$ r are the numbers of pixels of an image and a target sub-image, respectively.
Quantum Information Processing – Springer Journals
Published: Dec 7, 2013
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