Meaningful ciphertext image encryption via ND-ICNTC chaos and histogram reorganization with steganalysis-based evaluation

To address the common limitations of existing visually meaningful ciphertext image encryption schemes, including low ciphertext quality and limited steganalysis resistance, this paper proposes a visually meaningful ciphertext image encryption algorithm based on an N -dimensional infinite-collapse non-adjacent three-term coupling (ND-ICNTC) chaotic system and a histogram-reorganizing strategy. The plaintext image is converted into a noise-like ciphertext via compression, histogram reconstruction, and bit-level scrambling and then embedded into a cover image. The histogram reconstruction and scrambling significantly expand the pixel-value distribution, enhancing distinguishability from conventional ciphertexts and improving data security, while also providing a more favorable embedding distribution that enhances visual quality. The ND-ICNTC system features large Lyapunov exponents, wide chaotic parameter range, uniformly distributed attractors, and strong randomness, while its non-adjacent three-term coupling balances diffusion rate and computational cost. Comprehensive security analyses, including cryptographic evaluation and statistical/learning-based steganalysis, confirm high security, superior visual quality, and strong undetectability.