Data Hiding Based on Subsampling and Compressive Sensing

Author

Wei Li ; Jeng-Shyang Pan ; Lijun Yan ; Chun-Sheng Yang ; Hsiang-Cheh Huang

Author_Institution

Sch. of Comput. Sci. & Technol., Harbin Inst. of Technol., Shenzhen, China

fYear

2013

fDate

16-18 Oct. 2013

Firstpage

611

Lastpage

614

Abstract

This paper proposes a novel scheme that considers the data hiding with sub sampling and compressive sensing. We utilize the characteristics of compressive sensing, sparsity and random projection, to embed secret data in the observation domain of the sparse image obtained through compressive sensing. The high bit correction rate (BCR) in experiments shows the high accuracy of our proposed method.

Keywords

compressed sensing; data encapsulation; image sampling; BCR; bit correction rate; compressive sensing; random projection; secret data hiding; sparse image domain; subsampling; Compressed sensing; Data mining; Equations; Image coding; Mathematical model; Multimedia communication; Watermarking; compressive sensing; data hiding; sparse decomposition; subsampling;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Information Hiding and Multimedia Signal Processing, 2013 Ninth International Conference on

Conference_Location

Beijing

Type

conf

DOI

10.1109/IIH-MSP.2013.157

Filename

6846713

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=692076