Abstract: In this paper, an optimized multi-pass pixel value ordering (PVO) algorithm based on spatial position is proposed. The target image is first divided into multiple subblocks of 3 ￡ 3 pixels. By fully integrating the spatial positions of each pixel, all pixels are partitioned into two groups for two rounds of embedding. In the first round, the edge pixels of the pixel block are predicted and embedded based on their spatial positions. In the second round, some pixel values are regenerated first, and then the middle pixels are sorted and embedded according to the multi-pass pixel value ordering algorithm, thereby fully exploiting the correlation between spatial position and pixel value size. Experimental results show that the regeneration of pixel values improves the embedding efficiency in the multi-pass sorting algorithm. While ensuring reversibility, the proposed algorithm not only enhances the embedding capacity, but also achieves excellent peak signal to noise ratio performance, ensuring the image quality after embedding and meeting practical application requirements.

Key words: reversible data hiding, pixel value ordering, spatial location optimization, multi-pass prediction, prediction error, embedding capacity