Improving Multi-Histogram-Based Reversible Watermarking Using Optimized Features and Adaptive Clustering Number

Improving Multi-Histogram-Based Reversible Watermarking Using Optimized Features and Adaptive Clustering Number

For the multi-histogram-based reversible watermarking (MHRW) scheme, the performance greatly depends on the multi-histogram construction, which remains a challenge in this field. To generate more desirable multi-histograms, this paper improves the MHRW using the Fuzzy C-Means (FCM) clustering techni...

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Bibliographic Details
Main Authors: Weili Wang, Chuntao Wang, Junxiang Wang, Shan Bian, Qiong Huang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Reversible watermarking
multiple histograms
prediction error
fuzzy C-means clustering
local feature
Online Access:https://ieeexplore.ieee.org/document/9139944/

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