<p>With the rapid growth of multimedia communication, ensuring the confidentiality and integrity of digital images has become a pressing challenge in information security. Traditional cryptographic algorithms are often inadequate for image data due to inherent properties such as high redundancy and strong pixel correlations. In response, researchers have explored unconventional paradigms such as chaotic systems, DNA-based schemes, and machine learning to address these challenges. This paper presents a novel image encryption framework that synergistically combines a one-dimensional Improved sine chaotic map with an origami-inspired confusion mechanism. The proposed chaotic map exhibits complex dynamical behavior, including high sensitivity to initial conditions and parameters, a large key space, and robust pseudo-randomness, as confirmed through rigorous mathematical and numerical analyses. The origami-based confusion strategy introduces geometrically controlled permutations of pixel positions, inspired by folding and unfolding operations in traditional origami, thereby significantly enhancing the entropy and diffusion characteristics of the cipher image. Experimental evaluations on standard benchmark images demonstrate the algorithm’s effectiveness, achieving near-ideal metrics for information entropy, correlation coefficients, Number of Pixels Change Rate (NPCR), Unified Average Changing Intensity (UACI), and Structural Similarity Index Measure (SSIM). The proposed method offers a highly secure solution for real-time image encryption, suitable for applications in secure image transmission, surveillance, and medical imaging systems.</p>