Reversible data hiding based on pixel value similarity ordering and ordered collection

Abstract

In pixel value ordering (PVO)-based reversible data hiding (RDH), a smoother pixel sequence enhances embedding capacity and visual quality. Existing global PVO-based RDH methods use pixel complexity values for secondary ordering, which inaccurately reflect pixel value size, reducing sequence smoothness. This study proposes a pixel value similarity (PVS) ordering method to improve secondary pixel ordering. A value feature set is constructed for each pixel, and pixel value similarity is calculated to place pixels with the closest PVS adjacently. Additionally, a pixel ordered collection (POC) strategy organizes pixels in subsequences to increase expanded prediction errors, boosting embedding capacity. Experimental results demonstrate that PVS ordering yields smoother pixel sequences, with lower standard deviation (SD) and sum of absolute differences (SAD) compared to complexity-based methods. The proposed PVS and POC strategies enhance marked image quality, on the Kodak image dataset achieving an average peak signal-to-noise ratio (PSNR) of 61.38 dB with 20,000 bits embedding capacity.