A Novel High-Capacity Data Hiding in Encrypted Images Based on Compressive Sensing Progressive Recovery
Di Xiao, Fei Li, Mengdi Wang, Hongying Zheng
Abstract
Due to the emergence of visual privacy issues, encrypted image processing has attracted a lot of attention. Data hiding in encrypted images (DHEI) is an effective method to embed secret data in the encrypted domain and protect the image privacy. However, existing methods do not allow a large amount of embedding capacity. In this letter, we propose a novel DHEI scheme utilizing prediction coding based on compressive sensing (CS) progressive recovery. The original image is pre-processed using CS prediction technique to create spare room, and then the image is encrypted and sent to the data hider. Furthermore, the data hider could embed secret data into Most Significant Bits (MSBs) of the corresponding locations. In the decoding phase, the embedded data can be extracted without any distortion and the original image could be reconstructed. Experimental results demonstrate that our scheme can achieve a higher embedding capacity than other state-of-the-art schemes while keeping a considerable recovered image quality.