兼顾彩色图像质量和安全性的语义像素编码视觉秘密共享技术

Kanchan Patil, Jyotsna Barpute, Mrudul Arkadi, S. Bhirud, C. A, J. A., S. G., Shibani Raju S
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引用次数: 0

摘要

彩色图像被广泛应用于各个领域,包括数字媒体以及卫星和军事领域的关键应用。随着这些图像的重要性与日俱增,保护其内容免受未经授权的访问和潜在威胁的必要性也日益凸显。人们提出了视觉秘密共享(VSS)方案作为有效的机制,将图像加密为多个共享,每个共享不提供有关原始内容的任何信息。然而,传统的可视化秘密共享方法存在像素扩展等问题,导致复杂性增加,并可能影响图像质量。保持无可挑剔的图像质量之所以受到重视,主要是因为关键的应用决策往往基于图像细节的清晰度和准确性。为了应对这些挑战,我们提出了语义像素编码视觉秘密共享(SPEVSS)技术。通过将语义像素编码与 VSS 相结合,制定了一种稳健的机制,在保持原始图像保真度的同时,有效地抵御了像素扩展。这项研究大大降低了计算复杂度,提高了解密方法的效率,并为彩色图像建立了一个更稳健的安全框架。拟议的 SPEVSS 的性能显示,重建图像的 PSNR 达到了 42 dB,这说明该方法能够在安全性和最佳图像质量之间取得平衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Semantic pixel encoding visual secret sharing technique for balancing quality and security in color images
Color images are widely utilized across various domains, encompassing digital media and extending to critical applications in satellite and military arenas. As the significance of these images has grown, the need to protect their content from unauthorized access and potential threats has been underscored. Visual Secret Sharing (VSS) schemes have been proposed as effective mechanisms, with images being encrypted into multiple shares that, individually, offer no discernible information about the original content. Nevertheless, issues such as pixel expansion have been noted in traditional VSS methods, which result in increased complexity and a potential compromise in image quality. Maintaining impeccable image quality is emphasized, mainly since critical application decisions are often based on the clarity and accuracy of image details. The Semantic Pixel Encoding Visual Secret Sharing (SPEVSS) technique is proposed to address these identified challenges. A robust mechanism has been formulated through the integration of semantic pixel encoding with VSS, effectively countering pixel expansion while preserving the fidelity of the original image. As a result of this research, computational complexity has been significantly reduced, decryption methodologies have been made more efficient, and a more robust security framework for colour images has been established. The performance of the proposed SPEVSS shows the reconstructed images show the PSNR of 42 dB has been recorded in images processed, underscoring the method’s capability to balance security and optimal image quality.
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