A new cost function for spatial image steganography based on 2D-SSA and WMF

Guoliang Xie, Jinchang Ren, Stephen Marshall, Huimin Zhao, HuiHui Li

Research output: Contribution to journalArticlepeer-review

22 Downloads (Pure)


As an essential tool for secure communications, adaptive steganography aims to communicate secret information with the least security cost. Inspired by the Ranking Priority Profile (RPP), we propose a novel two-step cost function for adaptive steganography in this paper. The RPP mainly includes three rules, i.e. Complexity-First rule, the Clustering rule and the Spreading rule, to design a cost function. We use the two-dimensional Singular Spectrum Analysis (2D-SSA) and Weighted Median Filter (WMF) in designing the two-step cost function. The 2D-SSA is employed in selecting the key components and clustering the embedding positions, which follows the Complexity-First rule and the Clustering rule. Also, we deploy the Spreading rule to smooth the resulting image produced by 2D-SSA with WMF. Extensive experiments have shown the efficacy of the proposed method, which has improved performance over four benchmarking approaches against non-shared selection channel attack. It also provides comparable performance in selection-channel-aware scenarios, where the best results are observed when the relative payload is 0.3 bpp or larger. Besides, the proposed approach is much faster than other model-based methods.
Original languageEnglish
Pages (from-to)30604-30614
Number of pages11
JournalIEEE Access
Publication statusPublished - 18 Feb 2021


  • image steganography
  • feature extraction
  • singular spectrum analysis (SSA)
  • weighted median filtering (WMF)
  • ranking priority profile


Dive into the research topics of 'A new cost function for spatial image steganography based on 2D-SSA and WMF'. Together they form a unique fingerprint.

Cite this