Block-Wise Compression Of The Quantum Gray-Scale Image Using Lossy Preparation Approach

Quantum computing draws huge attention due to the multidimensional information processing capability of the processor at the same time. The main idea of quantum imaging is to represent pixel intensities and their state using standard quantum circuits. For a medium or larger size image, the state label circuit takes more qubits as well as requires a huge connection leading to circuit complexity. In this work, a block-wise lossy SCMNEQR (state connection modification novel enhanced quantum representation) approach has been proposed to address more qubit connection issues. The average computation time decreased by 99.66% and 7.39% compared to the JPEG and DCT-EFRQI approaches respectively. The experimental results show that it outperforms the DCT-EFRQI (discrete cosine transform- efficient flexible representation of the quantum image) approach in terms of both representation and compression due to the use of block-wise division of transfer coefficient and state label alongside a novel reset gate.