Reversible Data Hiding in Encrypted Images based on Interpolation Compression and Bits Distribution

Securing online data storage is paramount in the modern digital age, particularly when dealing with sensitive information. Reversible Data Hiding in Encrypted Images (RDHEI) emerges as a highly promising technological advancement that permits embedding confidential data within encrypted images. This study focuses on developing an RDHEI algorithm employing the interpolation method and bit distribution. Through the amalgamation of multiple interpolation algorithms, a comparative analysis is conducted to identify the optimal combination. This approach leverages interpolation for dimensional reduction within the image, thereby maximizing its storage capacity. Furthermore, the concealed data and the image can be restored to their original version utilizing the reverse algorithm. Experimental results demonstrated that linear interpolation and dimensional restoration using Lanczos interpolation yields the most favorable outcomes. These results showed significant achievements in an Embedding Rate (ER) score of up to 5,929 bits per pixel (bpp), a Structure Similarity Index (SSIM) score of 0.971, and a Peak Signal-to-Noise Ratio (PSNR) score of 38.722 dB. These results indicate that our proposed RDHEI algorithm can be a practical approach for data hiding.