Reversible Data Hiding Method for Interpolated Images Based on Modulo Operation and Prediction-Error Expansion

Abstract

Image reversible data hiding (RDH) using interpolation technology (IT) provides high singlelayer embedding capacity and has become a research hotspot. To solve serious image distortion in existing methods caused by secondary embedding based on interpolated pixels, we propose an RDH method for interpolated images based on modulo operation and prediction-error expansion (PEE). Our method differs from existing RDH methods that only consider embedding data into interpolated pixels. First, an image interpolation method is used to generate an interpolated image, which is partitioned into overlapping 3 × 3 blocks. For each block, secret data are embedded into interpolated pixels using the modulo operation and into reference pixel using the PEE. Standard grayscale images of size 512 × 512 were selected from the popular BossBase and BOWS-2 image databases as input images for experiments. Extensive experimental results show that the proposed method avoids pixel values underflow/overflow caused by embedding data and reduces image distortion effectively. For each standard test image, the maximum bits per pixel (BPP) is higher than 1.5, and the corresponding peak signal to noise ratio (PSNR) is higher than 45.0 dB. At the given embedding capacity, the proposed method outperforms recent similar methods regarding the watermarked image quality. Moreover, the proposed method can resist histogram analysis, and the subjective evaluation proves that the proposed method has good imperceptibility.INDEX TERMS Reversible data hiding, interpolated image, modulo operation, prediction-error expansion.

High-Payload Data-Hiding Scheme Based on Interpolation and Histogram Shifting

“…e = t − P td (7) Step 6. The binary secret bit is embedded into the prediction error e, and a new prediction error e' is obtained based on Equation (8).…”

“…Sometimes, permanent distortion cannot be tolerated; therefore, many different reversible data-hiding schemes have been proposed. These data-hiding schemes are meant to extract information and recover the cover image in a lossless manner [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21]. Some of these reversible data-hiding schemes (RDH) include difference expansion (DE); histogram shifting (HS) [6], from which the proposed method draws some ideas; prediction error (PE) [7,10,19], from which some ideas were drawn; and pixel value ordering (PVO) [13][14][15][16]20,21], which shall be compared with the proposed method in the results section of this paper.…”

“…The above schemes can generate different types of resolution images. Although not mentioned above, one scheme to generate high-resolution images is image interpolation [8,12]. It is, therefore, needless to say that interpolation can be used in combination with other schemes to generate a better algorithm with a good imperceptibility and embedding capacity.…”