Secure Image Encryption Model with Compressive Sensing and Addition of Watermarking Approach - Shaik Kashif Hussain (International Journal of Intelligent Systems and Applications in Engineering, 2024)
In modern times, protecting medical images is essential to maintaining the accuracy of patient confidential data. One effective method for content-based authentication is watermarking. Multimedia files are first watermarked and then deleted for authentication reasons, according to the conventional watermarking procedure. Conventional watermarking models perform poorly due to their resilience and recovery capabilities, and there is currently no digital watermarking solution that provides total security from any type of attack. To solve these problems, including tamper localization and recovery, novel image authentication based on compressive sensing and watermarking is used. The novel image encryption technique presented in this paper is based on the idea of tamper localization. By detecting and eliminating illegal image modifications, tampering localization is essential for improving image quality. This article presents an ADTCWT, an adaptive dual-tree complex wavelet transform, which splits the input picture into high-frequency and low-frequency versions. In this scenario, the ISEO fine-tunes the ADTCWT’s parameters. The processed low- and high-frequency pictures are encrypted using the adaptive 2D logistic chaotic encryption (A-2DLCE) model. The improved ISEO is used to choose the keys for encryption. After that, you may get the original images back by doing an inverse decomposition with the inverse ADTCWT. Also, A-2DLCE gets the encrypted data so that it can decode the images. The reconstructed watermark has very little visible deformation, which keeps it authentic. The experiment showed that the proposed method is less visible and more durable than the present watermarking methods.