  Quantum image processing draws a lot of attention due to faster data
computation and storage compared to classical data processing systems.
Converting classical image data into the quantum domain and state label
preparation complexity is still a challenging issue. The existing techniques
normally connect the pixel values and the state position directly. Recently,
the EFRQI (efficient flexible representation of the quantum image) approach
uses an auxiliary qubit that connects the pixel-representing qubits to the
state position qubits via Toffoli gates to reduce state connection. Due to the
twice use of Toffoli gates for each pixel connection still it requires a
significant number of bits to connect each pixel value. In this paper, we
propose a new SCMFRQI (state connection modification FRQI) approach for further
reducing the required bits by modifying the state connection using a reset gate
rather than repeating the use of the same Toffoli gate connection as a reset
gate. Moreover, unlike other existing methods, we compress images using
block-level for further reduction of required qubits. The experimental results
confirm that the proposed method outperforms the existing methods in terms of
both image representation and compression points of view.

Quantum Physics;Computer Vision and Pattern Recognition;Computers and Society