Reducing location map in prediction-based difference expansion for reversible image data embedding

In this paper, we present a reversible data embedding scheme based on an adaptive edge-directed prediction for images. It is known that the difference expansion is an efficient data embedding method. Since the expansion on a large difference will cause a significant embedding distortion, a location...

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Bibliographic Details
Published in:Signal processing 2012-03, Vol.92 (3), p.819-828
Main Authors: Liu, Minglei, Seah, Hock Soon, Zhu, Ce, Lin, Weisi, Tian, Feng
Format: Article
Language:English
Subjects:
Applied sciences
Cryptography
Detection, estimation, filtering, equalization, prediction
Difference expansion
Distortion
Error detection
Exact sciences and technology
Information, signal and communications theory
Location map
Pattern recognition
Payloads
Permissible error
Pixels
Position (location)
Prediction error
Reversible data embedding
Signal and communications theory
Signal processing
Signal, noise
Telecommunications and information theory
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Summary:In this paper, we present a reversible data embedding scheme based on an adaptive edge-directed prediction for images. It is known that the difference expansion is an efficient data embedding method. Since the expansion on a large difference will cause a significant embedding distortion, a location map is usually employed to select small differences for expansion and to avoid overflow/underflow problems caused by expansion. However, location map bits lower payload capacity for data embedding. To reduce the location map, our proposed scheme aims to predict small prediction errors for expansion by using an edge detector. Moreover, to generate a small prediction error for each pixel, an adaptive edge-directed prediction is employed which adapts reasonably well between smooth regions and edge areas. Experimental results show that our proposed data embedding scheme for natural images can achieve a high embedding capacity while keeping the embedding distortion low. ► We present a reversible data embedding scheme based on difference expansion. ► We use an adaptive edge-directed prediction to generate small prediction errors. ► Edge detectors are used to reduce location map bits. ► Less location maps may improve PSNR-payload performance and justified by experiments.
ISSN:0165-1684
1872-7557
DOI:10.1016/j.sigpro.2011.09.028