Minimizing the Stego-Image Quality Impact of Message Embedding Using the DM Allocation Method

Recently, reversible image transformation (RIT) technology has attracted considerable attention because it is able not only to generate stego-images that look similar to target images of the same size, but also to recover the secret image losslessly. Therefore, it is very useful in image privacy protection and reversible data hiding in encrypted images. However, the amount of accessorial information, for recording the transformation parameters, is very large in the traditional RIT method, which results in an abrupt degradation of the stego-image quality. In this paper, an improved RIT method for reducing the auxiliary information is proposed. Firstly, we divide secret and target images into non-overlapping blocks, and classify these blocks into K classes by using the K-means clustering method. Secondly, we match blocks in the last (K-T)-classes using the traditional RIT method for a threshold T, in which the secret and target blocks are paired with the same compound index. Thirdly, the accessorial information (AI) produced by the matching can be represented as a secret segment, and the secret segment can be hided by patching blocks in the first T-classes. Experimental results show that the proposed strategy can reduce the AI and improve the stego-image quality effectively.

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Analysis of Least Significant Bit Method Using Sequential Encoding-Decoding in Steganography Digital Image

Proceeding International Conference on Science and Engineering ◽

10.14421/icse.v3.498 ◽

2020 ◽

Vol 3 ◽

pp. 201-205

Author(s):

Nurmi Hidayasari ◽

Febi Yanto

Keyword(s):

Image Quality ◽

Signal To Noise Ratio ◽

Maximum Size ◽

Least Significant Bit ◽

Relevant Research ◽

Stego Image ◽

Check Size ◽

Image Histogram ◽

Hide Data ◽

Histogram Testing

The method of steganography commonly used to hide data or information is Least Significant Bit (LSB) method. One of the relevant research is LSB using sequential Encoding - Decoding by David Pipkorn and Preston Weisbrot. In this research, an analysis of the LSB method using Sequential Encoding - Decoding by doing some testing. The tests are on the aspect of message security using tools StegSpy and enhanced LSB algorithm, testing on image quality by calculating the Peak Signal to Noise Ratio (PSNR) value and see the image histogram, testing on robustness of message by doing some image processing operations on stego image, like cropping, rotating, and etc, and then testing on capacity to check size of cover image and stego image and calculates the maximum size of data that can be hidden. From the testing process, we know that there are deficiencies in the aspects of security, robustness and capacity of a message. And then in this research we try to change the location of messages that are hidden in the image bits, which previous research used the 8th bit of each bytes, changed to the 7th bit. To be able to correct deficiencies in the security aspect. After repairing and testing like before, obtained better results in the security aspect. This can be seen from the image of the enhanced LSB algorithm process, the message is not detected, but unfortunately the image quality is reduced, with the low PSNR value generated.

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Image Steganography Method to Improve the Stego Image Quality and Security using Reversible Texture Synthesis

International Journal of Computer Applications ◽

10.5120/ijca2016911247 ◽

2016 ◽

Vol 147 (14) ◽

pp. 9-11

Author(s):

V. Lokeswara ◽

K. Tejaswi

Keyword(s):

Image Quality ◽

Texture Synthesis ◽

Image Steganography ◽

Stego Image

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Reversible data hiding method based on pixel expansion and homomorphic encryption

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-191478 ◽

2020 ◽

Vol 39 (3) ◽

pp. 2977-2990

Author(s):

R. Anushiadevi ◽

Padmapriya Praveenkumar ◽

John Bosco Balaguru Rayappan ◽

Rengarajan Amirtharajan

Keyword(s):

Image Quality ◽

Data Hiding ◽

Reversible Data Hiding ◽

Signal To Noise Ratio ◽

Homomorphic Encryption ◽

Secret Message ◽

Pixel Expansion ◽

Stego Image ◽

Encrypted Image ◽

Location Map

Digital image steganography algorithms usually suffer from a lossy restoration of the cover content after extraction of a secret message. When a cover object and confidential information are both utilised, the reversible property of the cover is inevitable. With this objective, several reversible data hiding (RDH) algorithms are available in the literature. Conversely, because both are diametrically related parameters, existing RDH algorithms focus on either a good embedding capacity (EC) or better stego-image quality. In this paper, a pixel expansion reversible data hiding (PE-RDH) method with a high EC and good stego-image quality are proposed. The proposed PE-RDH method was based on three typical RDH schemes, namely difference expansion, histogram shifting, and pixel value ordering. The PE-RDH method has an average EC of 0.75 bpp, with an average peak signal-to-noise ratio (PSNR) of 30.89 dB. It offers 100% recovery of the original image and confidential hidden messages. To protect secret as well as cover the proposed PE-RDH is also implemented on the encrypted image by using homomorphic encryption. The strength of the proposed method on the encrypted image was verified based on a comparison with several existing methods, and the approach achieved better results than these methods in terms of its EC, location map size and imperceptibility of directly decrypted images.

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Stego image quality and the reliability of PSNR

2010 2nd International Conference on Image Processing Theory, Tools and Applications ◽

10.1109/ipta.2010.5586786 ◽

2010 ◽

Cited By ~ 26

Author(s):

Adel Almohammad ◽

Gheorghita Ghinea

Keyword(s):

Image Quality ◽

Stego Image

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Efficient cover image selection based on spatial block analysis and DCT embedding

EURASIP Journal on Image and Video Processing ◽

10.1186/s13640-019-0486-8 ◽

2019 ◽

Vol 2019 (1) ◽

Cited By ~ 1

Author(s):

Sa’ed Abed ◽

Suood Abdulaziz Al-Roomi ◽

Mohammad Al-Shayeji

Keyword(s):

Image Quality ◽

Relative Entropy ◽

Detection Rate ◽

Image Representation ◽

Visual Image ◽

Cover Image ◽

Stego Image ◽

Pixel Intensity ◽

Secret Image ◽

Local Block

AbstractIn steganography, the cover medium is widely treated as a mere container for the embedded information, even though it affects the stego-image quality, security, and robustness. In addition, there is no consensus on the characteristics of a suitable cover image. In this work, we introduce and practically prove the most suitable cover image (MSCI) framework to automatically select a cover image for a given secret image. This paper proposes choosing the most suitable cover from a set of images based on two steps. First, a set of cover images is filtered based on relative entropy and a histogram in order to identify the most suitable candidates. Second, the local block pixel intensity features of the candidates are analyzed to select the most suitable cover image. Furthermore, cover image local blocks were optimized, using rotation and flipping, during the embedding process to further improve stego-image representation. The proposed framework demonstrated high visual image quality when compared with existing solutions. Steganalysis tests indicated that the proposed solution for cover selection provided an increased resistance to modern steganalyzers with up to 30% lowered detection rate, which improved security.

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