LAUSR

AbstractThe flexible representation of quantum images (FRQI) and novel enhanced quantum representation (NEQR) are well-known models used for storing and processing quantum images. In this article, we establish that the complexity of image preparation in FRQI model is $$O(n2^{2n})$$O(n22n), which is linear in the size of image. Moreover, by analyzing the FRQI and NEQR models, we propose an improved flexible representation of quantum images (IFRQI) which uses p qubits to store grayscale value of every pixel of a 2p-bit-deep image. The grayscale values are encoded by employing rotation matrices corresponding to chosen values of angles which assist in accurate retrieval of original image information through projective measurements. The quantum image compression algorithm and basic image processing operations are discussed in detail to establish the effectiveness of IFRQI model. The performance analysis in respect of time and space complexity exhibits that the IFRQI model is comparable to FRQI and NEQR models.