The need for secret sharing using meaningful shadow images is an important method to protect the transmitted data that does not attract the attention of adversary, which has become obvious in the past few years. The recovery of the cover image without any distortion and security of the embedded secret string efficiently needs to be addressed.

This paper proposes an invertible $(k,n)$ secret sharing scheme using meaningful shadow image based on Sorted Indexed Code (SIC) with high embedding capacity. The SIC helps to achieve better randomness between shadow images in terms of NPCR, the closeness of each objective assessment (i.e., PSNR, SSIM, NPCR, and UACI) between the shadows. Hence, by utilizing the SIC and polynomial based threshold secret sharing method the proposed scheme achieves an adequate visual quality of shadow images, complete recovery of the cover image, and increases the embedding capacity. The experimental results show the visual quality of image shares for camouflage purpose of steganography. The visual qualities of shadow images for the proposed scheme are validated through Peak-Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Method (SSIM) analysis. Further, the security of the proposed scheme is analyzed using dissimilarity measures; Number of Pixel Change Rate (NPCR) and Unified Average Changing Intensity (UACI).

使用有意义的阴影图像进行秘密共享的需求是保护传输数据的一种重要方法，这种传输方法不会引起对手的注意，这在过去几年中变得越来越明显。需要有效地解决封面图像的恢复问题，而又不能有效地解决嵌入秘密字符串的任何失真和安全问题。

本文提出了一个可逆的 $（ķ，ñ）$基于具有高嵌入能力的基于排序索引码（SIC）的有意义的阴影图像的秘密共享方案。SIC有助于在阴影图像之间实现更好的随机性，包括NPCR，阴影之间每个客观评估（即PSNR，SSIM，NPCR和UACI）的紧密度。因此，通过利用基于SIC和基于多项式的阈值秘密共享方法，所提出的方案实现了阴影图像的足够的视觉质量，覆盖图像的完全恢复，并且增加了嵌入能力。实验结果表明，用于隐写术的图像共享的视觉质量。通过峰信噪比（PSNR）和结构相似指数法（SSIM）分析，验证了该方案阴影图像的视觉质量。进一步，拟议方案的安全性采用相异措施进行分析；像素变化率（NPCR）和统一平均变化强度（UACI）数。