Image steganography plays a vital role in securing secret data by embedding it in the cover images. Usually, these images are communicated in a compressed format. Existing techniques achieve this but have low embedding capacity. Enhancing this capacity causes a deterioration in the visual quality of the stego-image. Hence, our goal here is to enhance the embedding capacity while preserving the visual quality of the stego-image. We also intend to ensure that our scheme is resistant to steganalysis attacks. This paper proposes a Compressed Sensing Image Steganography (CSIS) scheme to achieve our goal while embedding binary data in images. The novelty of our scheme is the combination of three components in attaining the above-listed goals. First, we use compressed sensing to sparsify cover image block-wise, obtain its linear measurements, and then uniquely select permissible measurements. Further, before embedding the secret data, we encrypt it using the Data Encryption Standard (DES) algorithm, and finally, we embed two bits of encrypted data into each permissible measurement. Second, we propose a novel data extraction technique, which is lossless and completely recovers our secret data. Third, for the reconstruction of the stego-image, we use the least absolute shrinkage and selection operator (LASSO) for the resultant optimization problem. We perform experiments on several standard grayscale images and a color image, and evaluate embedding capacity, PSNR value, mean SSIM index, NCC coefficients, and entropy. We achieve 1.53 times more embedding capacity as compared to the most recent scheme. We obtain an average of 37.92 dB PSNR value, and average values close to 1 for both the mean SSIM index and the NCC coefficients, which are considered good. Moreover, the entropy of cover images and their corresponding stego-images are nearly the same.

中文翻译：

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CSIS：基于压缩感知的增强嵌入能力图像隐写方案

图像隐写术通过将秘密数据嵌入到封面图像中，在保护秘密数据方面起着至关重要的作用。通常，这些图像以压缩格式进行通信。现有技术可以实现这一点，但嵌入能力却很低。增强此能力会导致隐秘图像的视觉质量下降。因此，我们的目标是在保持隐身图像的视觉质量的同时，增强嵌入能力。我们还打算确保我们的方案能够抵抗隐写分析攻击。本文提出了一种压缩感知图像隐写术（CSIS）方案来实现我们的目标，同时将二进制数据嵌入图像中。我们方案的新颖之处在于实现上述目标的三个要素的结合。首先，我们使用压缩感应来按块稀疏覆盖图像，获得其线性测量值，然后唯一选择允许的测量值。此外，在嵌入机密数据之前，我们使用数据加密标准（DES）算法对其进行加密，最后，将两位加密数据嵌入到每个允许的度量中。其次，我们提出了一种新颖的数据提取技术，该技术无损且可以完全恢复我们的秘密数据。第三，对于隐身图像的重建，我们使用最小绝对收缩和选择算子（LASSO）来解决优化问题。我们在几个标准灰度图像和彩色图像上进行实验，并评估嵌入能力，PSNR值，平均SSIM指数，NCC系数和熵。与最新方案相比，我们实现了1.53倍的嵌入容量。我们获得了37.92 dB的PSNR平均值，平均SSIM指数和NCC系数的平均值均接近1，这被认为是不错的。此外，封面图像及其对应的隐秘图像的熵几乎相同。