JPEG Steganography Based on Adaptive Cover Selection Using Haar Wavelet Domain Indicators
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Fujian Natural Science Foundation Program Youth Innovation Project (2018J05112); National Natural Science Foundation of China (61402390, U1636102); National Key Technology R&D Program of China (2014BAH41B01); National Key Research and Development Program of China (2016YFB0801003)

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    Abstract:

    The existing steganographic cover selection indicators based on image texture complexity modeling are not compatible with JPEG steganography. To solve this problem, a JPEG steganography is proposed based on cover selection using Haar wavelet domain indicators. This method establishes the relationship of JPEG image pixels by taking high-ordered Haar wavelet translation as the model, and calculates the average norm of the decomposition image matrix in each direction to select highly undetectable covers. Moreover, the proposed indicator, which performs better than most of the existing models in the inter pixel modeling ability, can enhance the concealment of JPEG steganography in cover selection. Experimental results show that, in most cases, the proposed JPEG steganography using cover selection achieves higher concealment than that without selecting covers by an average value of about 7.7%. This figure has higher concealment than the existing cover selection indicators by an average value of 2.0%. Therefore, the proposed steganography attains better concealment.

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黄炜,赵险峰.基于Haar小波域指标自适应选择载体的JPEG隐写.软件学报,2018,29(8):2501-2510

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History
  • Received:September 14,2016
  • Revised:December 10,2016
  • Adopted:
  • Online: July 20,2017
  • Published:
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