Hybrid Predictor and Field-Biased Context Pixel Selection Based on PPVO

Abstract

Most pixel-value-ordering (PVO) predictors generated prediction-errors including −1 and 1 in a block-by-block manner. Pixel-based PVO (PPVO) method provided a novel pixel scan strategy in a pixel-by-pixel way. Prediction-error bin 0 is expanded for embedding with the help of equalizing context pixels for prediction. In this paper, a PPVO-based hybrid predictor (HPPVO) is proposed as an extension. HPPVO predicts pixel in both positive and negative orientations. Assisted by expansion bins selection technique, this hybrid predictor presents an optimized prediction-error expansion strategy including bin 0. Furthermore, a novel field-biased context pixel selection is already developed, with which detailed correlations of around pixels are better exploited more than equalizing scheme merely. Experiment results show that the proposed HPPVO improves embedding capacity and enhances marked image fidelity. It also outperforms some other state-of-the-art methods of reversible data hiding, especially for moderate and large payloads.

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

“…In the context of images, the peak signal-to-noise ratio (PSNR) [13][14][15][16][17][18] is commonly employed to assess the distortion introduced in image steganography. A lower PSNR value indicates a more distorted image.…”

“…Refs. [13][14][15][16]20,21] all describe reversible data-hiding methods in the histogram shifting and/or interpolation domains. All of these methods can produce very high PSNR values and high embedding capacities.…”

“…Table 3 shows a comparison of the proposed method with these other previously proposed methods. HPPVO [13] has an average EC of 37,995 bits, OPPVO [14] has an average PSNR value of 30,555 bits, IPPVO [15] has an average EC of 33,723 bits, IPVO [16] has an average EC value of 32,218 bits, GS-LPVO [20] has an average EC value of 34,301, and LPVO [21] has an average EC value of 43,006, while the proposed method has a high EC of 101,283.5 bits. As can be seen, the proposed method has the highest average EC value when compared to these methods; thus, the proposed method is superior to the compared methods with regard to the embedding capacity.…”

“…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.…”

“…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. Reversible data hiding [15] involves embedding information into host data while maintaining the ability to fully recover both the original host data and the hidden information.…”