Sorting methods and adaptive thresholding for histogram based reversible data hiding
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Sorting methods and adaptive thresholding for histogram based reversible data hiding Ammar Mohammadi 1 & Mansor Nakhkash 1 Received: 10 December 2019 / Revised: 11 August 2020 / Accepted: 25 August 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract
This paper presents a histogram based reversible data hiding (RDH) scheme, which divides image pixels into different cell frequency bands to sort them for data embedding. Data hiding is more efficient in lower cell frequency bands because it provides prediction that is more accurate. Using pixel existence probability for some pixels of ultra-low cell frequency band, another sorting is performed. Employing these two novel sorting methods, we determine smooth areas of an image more efficient than other schemes. The smoother area of the image is selected for data embedding, the less distortion of the marked image may be achieved. In another proposal, we introduce hiding intensity analysis to determine optimum prediction error to embed data. In comparison with methods that sequentially choose prediction error, this analysis results in better quality of the marked image. In effect, the proposed scheme increases the hiding capacity for a specific level of the distortion comparing to existent RDH algorithms. Experimental results confirm that the proposed algorithm outperforms state of the art ones. Keywords Reversible data hiding . Embedded capacity . Histogram modification
1 Introduction Data hiding is to embed data in a cover medium such as audio, multimedia, image, and textual files. Embedding data in image has many applications, such as copyright protection, authentication and cover communication. The original cover image in many applications of data hiding is not required to be restored [1, 2]. However, there exist applications in medical image sharing, multimedia archive management and so on, which need the restoration of the cover without any distortion. Reversible data hiding (RDH) is an approach that addresses the methods for complete restoration of the original cover after the extraction of embedded data.
* Mansor Nakhkash [email protected]
1
Department of Electrical Engineering, Yazd University, Yazd, Iran
Multimedia Tools and Applications
There are various RDH methods [23]; but the more developed methods can be classified into two main categories: the methods based on 1- DE (difference expansion) [25] and 2histogram modification [20]. In addition to this grouping, the two main DE and histogram based techniques can be combined with prediction-error expansion [3–5, 13, 18, 22, 24, 33], lossless compression [7, 10, 16, 30–32], code division multiplexing [19] and prediction-error modification [8, 9, 12, 14, 15, 17, 21, 26–29]. The difference expansion (DE) was proposed by Tian [25] in 2003. In DE, the image is divided into pairs of pixels, in which the data bits are embedded. This method embeds one bit into a pixel pair and thus a hiding rate up to 0.5 bit per pixel can be realized. Tian exploits a location map to record the se
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