Quantum image scaling using nearest neighbor interpolation
Although image scaling algorithms in classical image processing have been extensively studied and widely used as basic image transformation methods, the quantum versions do not exist. Therefore, this paper proposes quantum algorithms and circuits to realize the quantum image scaling based on the improved novel enhanced quantum representation (INEQR) for quantum images. It is necessary to use interpolation in image scaling because there is an increase or a decrease in the number of pixels. The interpolation method used in this paper is nearest neighbor which is simple and easy to realize. First, NEQR is improved into INEQR to represent images sized \(2^{n_{1}} \times 2^{n_{2}}\). Based on it, quantum circuits for image scaling using nearest neighbor interpolation from \(2^{n_{1}} \times 2^{n_{2}}\) to \(2^{m_{1}} \times 2^{m_{2}}\) are proposed. It is the first time to give the quantum image processing method that changes the size of an image. The quantum strategies developed in this paper initiate the research about quantum image scaling.
image scaling nearest neighbor interpolation quantum circuit quantum image processing quantum computation