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<p>In recent years, image encryption schemes based on compressive sensing (CS) have garnered extensive research. However, existing algorithms still have some issues, including poor image reconstruction quality and inadequate security. To address these issues, this paper proposes a novel image encryption algorithm that integrates chaotic system with block compressive sensing. First, a new two-dimensional mod composite cosine model (2D-MCCM) is designed. Its complex dynamic characteristics are revealed through nonlinear dynamics tools such as Lyapunov exponent (LE), bifurcation diagram, trajectory diagram and NIST. Research results indicate that the 2D-MCCM possesses complex chaotic characteristics. Then, to mitigate the issue of poor image reconstruction quality caused by the CS, this paper constructs a new measurement matrix. Finally, this paper proposes a novel image encryption algorithm, which incorporates DNA encoding and S-box technology to enhance security. Performance analysis indicates that the average peak signal-to-noise ratio and structural similarity index metric of different reconstructed images reach approximately 36 dB and 0.909 at a 0.5 compression rate, respectively. The information entropy of cipher images exceeds 7.9970, while the values of NPCR and UACI achieve 99.6100<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\%\)</EquationSource> <EquationSource Format="MATHML"><math> <mo>%</mo> </math></EquationSource> </InlineEquation> and 33.4767<InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\%\)</EquationSource> <EquationSource Format="MATHML"><math> <mo>%</mo> </math></EquationSource> </InlineEquation>. Simulation results demonstrate that the proposed algorithm exhibits excellent compression performance and security.</p>

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A novel chaotic image encryption scheme based on block compressive sensing

  • 期刊论文

  • 发表日期：

    2026年2月26日

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  • Jianeng Tang,
  • Jinyuan Lin,
  • Yijun Hong,
  • Jianan Hou,
  • Yinghang Zhao

摘要

In recent years, image encryption schemes based on compressive sensing (CS) have garnered extensive research. However, existing algorithms still have some issues, including poor image reconstruction quality and inadequate security. To address these issues, this paper proposes a novel image encryption algorithm that integrates chaotic system with block compressive sensing. First, a new two-dimensional mod composite cosine model (2D-MCCM) is designed. Its complex dynamic characteristics are revealed through nonlinear dynamics tools such as Lyapunov exponent (LE), bifurcation diagram, trajectory diagram and NIST. Research results indicate that the 2D-MCCM possesses complex chaotic characteristics. Then, to mitigate the issue of poor image reconstruction quality caused by the CS, this paper constructs a new measurement matrix. Finally, this paper proposes a novel image encryption algorithm, which incorporates DNA encoding and S-box technology to enhance security. Performance analysis indicates that the average peak signal-to-noise ratio and structural similarity index metric of different reconstructed images reach approximately 36 dB and 0.909 at a 0.5 compression rate, respectively. The information entropy of cipher images exceeds 7.9970, while the values of NPCR and UACI achieve 99.6100 \(\%\) % and 33.4767 \(\%\) % . Simulation results demonstrate that the proposed algorithm exhibits excellent compression performance and security.