Online sequential Extreme learning Machine (OSELM) based denoising of encrypted image

Abstract

With the increasing demand for secure digital communication, image encryption is essential for safeguarding sensitive information from unauthorized access. Conventional encryption techniques frequently encounter difficulties when dealing with noise and maintaining image quality during transmission. This study presents an innovative approach to image encryption that integrates an Online Sequential Extreme Learning Machine (OSELM) autoencoder and chaotic systems with DNA code for enhanced image encryption and denoising. The proposed method amalgamates an OSELM autoencoder, a hyperchaotic system incorporating two mersisters, a two-dimensional sine map, and DNA coding to effectively protect images from various types of noise such as Gaussian, Salt and Pepper, Quantization, Speckle, Sensor, and Environmental noises. OSELM-based denoising boosts encryption images’ resilience to noise attacks, ensuring strong security and image quality. Simulation results have shown that the proposed method achieved a key space of around 10²⁴⁰ or 2⁷⁹⁷, with information entropy values near 8 for encrypted images. This method also attains Number of Pixels Change Rate (NPCR) values between 99.59 % and 99.64 % and Unified Average Changing Intensity (UACI) values ranging from 32.97 % to 33.92 %, Peak Signal to Noise Ratio (PSNR) values of denoised images between 23.63 and 37.45, indicating outstanding performance in terms do both security and noise resilience. Additionally, histogram analysis, correlation analysis, and Mean Squared Error (MSE) results highlight the algorithm’s strong resistance to statistical attacks. At the same time, NPCR and UACI values affirm its robustness against differential attacks. The algorithm exhibits high sensitivity to key variations of up to 10^-16, ensuring robust protection even with slight changes to the encryption of the decryption key. Finally, the NIST SP800-22 statistical tests confirm the randomness of the encrypted image’s bitstream, reinforcing its cryptographic strength. This dual approach effectively addresses the challenges of image security and noise resilience, safeguarding the integrity and clarity of digital images. This makes it highly suitable for the secure transmission and storage of digital images in diverse fields such as medicine, photography, biology, astronomy, and defense.