2015
DOI: 10.7763/ijcte.2015.v7.981
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Novel Prediction Error Based Reversible Data Hiding Method Using Histogram Shifting

Abstract: Abstract-Reversible data hiding can recover the original image from the marked image without any distortion. This paper presents a novel prediction error based reversible data hiding method using histogram shifting in spatial domain. Three predictors including Mean, JPEG lossless and median edge detector (MED) are employed to compute prediction values for current pixels, respectively. Prediction errors are calculated as well to build histogram bins. Histogram shifting mechanism is designed that bins with large… Show more

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Cited by 6 publications
(4 citation statements)
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“…Take Figure 5b as an example. Through Equation (8), we know that the complexity of the large block is NL = max (7,19,56,56) − min (5,17,19,19) = 56 − 5 = 51. The computation flow is shown in Figure 5.…”
Section: Related Workmentioning
confidence: 99%
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“…Take Figure 5b as an example. Through Equation (8), we know that the complexity of the large block is NL = max (7,19,56,56) − min (5,17,19,19) = 56 − 5 = 51. The computation flow is shown in Figure 5.…”
Section: Related Workmentioning
confidence: 99%
“…It is assumed that the threshold values are T 2 = 15 and T 1 = 60. When the four sub-block pixel combination in the first 4 × 4 block is X 1 = {5, 4, 7, 17}, X 2 = {15, 19, 17, 54}, X 3 = {13, 19, 89, 56}, and X 4 = {19, 17, 56, 56}, and each sub-blocks are sorted individually; through Equation 8, the computed block complexity is NL = max (7,19,56,56) − min (5,17,19,19) = 51. When T 2 < NL ≤ T 1 , it conforms to the general complexity block in Case 2, hence the entire block is reordered.…”
Section: Related Workmentioning
confidence: 99%
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