A crosstalk-free multiple-image encryption scheme based on computational ghost imaging with binarized detection

Abstract

Crosstalk noise is a main problem limiting the performance of multiple-image encryption (MIE) scheme. In this work, we proposed a crosstalk-free MIE scheme based on computational ghost imaging (CGI) with binarized detection. In the encryption process, the plaintext images are encrypted into intensity sequences by the CGI system and quantified into two levels to obtain binary ciphertext sequences, which does not cause severe degradation in decrypted image quality compared to traditional CGI. Then, for the binary ciphertext sequences, we can combine them into a decimal grayscale ciphertext. To enhance security, a pixel bit layer scrambling (PBLS) algorithm is designed to scramble the grayscale ciphertext to obtain the final ciphertext. In the decryption process, anyone of the plaintext images can be decrypted without being affected by other plaintext images after performing inverse PBLS algorithm on the ciphertext and extracting the binary ciphertext sequence. The effectiveness, robustness, encryption capacity and security of the proposed scheme are demonstrated by numerical simulations and theoretical analysis.