Abstract
An adaptive error prediction method based on multiple linear regression algorithm to improve the reversible information hiding capacity is proposed. The inner relationship among pixels around the object pixel is learned adaptively based on the consistency feature of pixels distributing in local area of natural images, and a multiple linear regression function matrix is built to express the relationship. The object pixel is predicted accurately with the linear function learned from its neighboring pixels, rather than simply with the arithmetic combination of surrounding pixels. Experimental results show that the multiple linear regression based adaptive image error prediction algorithm can effectively enhance the reversible data embedding capability compared to other advanced error prediction methods.
Original language | English (US) |
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Pages (from-to) | 362-370 |
Number of pages | 9 |
Journal | Yingyong Kexue Xuebao/Journal of Applied Sciences |
Volume | 36 |
Issue number | 2 |
DOIs | |
State | Published - Mar 2018 |
All Science Journal Classification (ASJC) codes
- General Computer Science
- General Mathematics
- General Engineering
Keywords
- Embedding capacity
- Multiple linear regression
- Reversibility
- Reversible data hiding