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2015
DOI: 10.1016/j.jvcir.2014.09.005
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A new lossless data hiding method based on joint neighboring coding

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Cited by 7 publications
(4 citation statements)
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References 25 publications
(33 reference statements)
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“…Results show that this method achieved high capacity, small compression rate, high speed in the execution time for embedding/reconstruction and high quality of reconstructed image (Chang and Nguyen, 2014). Pan et al (2015) also proposed a reversible data hiding technique that hides secret bits into image.It uses side-match distortion to sort the VQ codebook to make the index very close to its neighbour and use the residual value between indexes for hiding that it is obtained from XOR operation. It preserves the quality of the reconstructed cover image and increases the hiding capacity (Pan et al, 2015).…”
Section: Compressed Domainmentioning
confidence: 97%
See 1 more Smart Citation
“…Results show that this method achieved high capacity, small compression rate, high speed in the execution time for embedding/reconstruction and high quality of reconstructed image (Chang and Nguyen, 2014). Pan et al (2015) also proposed a reversible data hiding technique that hides secret bits into image.It uses side-match distortion to sort the VQ codebook to make the index very close to its neighbour and use the residual value between indexes for hiding that it is obtained from XOR operation. It preserves the quality of the reconstructed cover image and increases the hiding capacity (Pan et al, 2015).…”
Section: Compressed Domainmentioning
confidence: 97%
“…Pan et al (2015) also proposed a reversible data hiding technique that hides secret bits into image.It uses side-match distortion to sort the VQ codebook to make the index very close to its neighbour and use the residual value between indexes for hiding that it is obtained from XOR operation. It preserves the quality of the reconstructed cover image and increases the hiding capacity (Pan et al, 2015).…”
Section: Compressed Domainmentioning
confidence: 99%
“…The simplicity in implementation and low cost of the operations are two important properties of the spatial domain techniques, but the drawback of this approach is low robustness against signal processing and geometric attacks. Instead, transformed domain techniques are usually employed for robust watermarking to ensure resistance of the watermarked image against the mentioned attacks [13,39,40]. Several examples of transformed domain techniques are the Discrete Cosine Transform (DCT), Singular Value Decomposition (SVD), Discrete Wavelet Transform (DWT) and Discrete Fourier Transform (DFT).…”
Section: Literature Reviewmentioning
confidence: 99%
“…According to Ki-Hyun Jung [13] the highest embedded capacity must be within the acceptable image quality and also the capacity of the embedding is restricted with the lower distortion of the image [11,14].The easiest way to hide data is to embed cipher texts by hiding bitmaps in colour picture [14]. Here the number of bits that is being traversed is perceived.…”
Section: Literature Surveymentioning
confidence: 99%