Revisit and Optimize the Visual Secret Sharing of Fuzzy Random Grids

Aiming at the problems of the existing visual secret sharing of fuzzy random grids (FRGVSS) scheme, such as insufficient algorithm design adaptability to the actual computing environment, and the obvious degradation of the visual quality of the decrypted image due to its internal mechanism, this study is based on the advantages of FRGVSS method in visual secret sharing. The algorithm structure was systematically analyzed and the FRGVSS algorithm was reconstructed, enhancing the algorithm’s adaptability to the computing environment. Meanwhile, in order to further enhance the visual quality of the decrypted image, this study introduces error diffusion technology to optimize the random grids shares generated during the encryption process, significantly improving the visual clarity and readability of the reconstructed image. The results of the visual quality assessment experiment show that the proposed scheme not only performs better in terms of the adaptability of the algorithm environment, but also can significantly improve the visual quality of the decrypted image.