A novel embedding technique for lossless data hiding in medical images employing histogram shifting method

2014 ◽  
Vol 12 (03) ◽  
pp. 1450026
Author(s):  
J. A. Alex Rajju Balan ◽  
S. Edward Rajan
Keyword(s):  
Data Hiding ◽  
High Frequency ◽  
Signal To Noise Ratio ◽  
Zero Point ◽  
Discrete Wavelet ◽  
Histogram Shifting ◽  
Histogram Modification ◽  
Modification Technique ◽  
Dct Coefficients ◽  
Lossless Data Hiding

In this paper, a lossless data hiding method based on histogram shifting for MR images using Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT) are presented. In this method, the algorithms are validated to hide the data in wavelet coefficients of high frequency subbands. This scheme has the advantage of comparing the DCT coefficients and the DWT coefficients which permit low distortion between the watermarked image and the original image. It also shifts a part of the histogram of high frequency subbands and embeds the data by using the created histogram zero point. To prevent the overflows and underflows in the spatial domain, caused by the modification of the DCT coefficients and the DWT coefficients, the histogram modification technique is applied. Therefore, we present a validated method to evaluate and compare the performance of DWT and DCT on task, in terms of data embedding payload and the Peak Signal to Noise Ratio (PSNR) in the medical image. A careful experimental analysis validates the method showing its superiority over the existing methods.

A High Capacity Reversible Data Hiding Scheme Based on Multi-Level Integer DWT and Histogram Modification

2014 ◽  
Vol 6 (1) ◽  
pp. 51-64 ◽  
Author(s):  
Shun Zhang ◽  
Tie-gang Gao ◽  
Fu-sheng Yang
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Wavelet Transformation ◽  
High Capacity ◽  
Discrete Wavelet ◽  
Embedding Capacity ◽  
Discrete Cosine Transformation ◽  
Histogram Modification ◽  
Multi Level ◽  
High Embedding Capacity

A reversible data hiding scheme based on integer DWT and histogram modification is proposed. In the scheme, the cover media is firstly transformed by Integer DWT (Discrete Wavelet Transformation); then information is embedded through the modification of histograms of the middle and high frequency sub-bands of the DWT coefficients. In order to increase the embedding capacity, a multi-level scheme is proposed, which achieved both high embedding capacity and reversibility. Extensive experimental results have shown that the proposed scheme achieves both higher embedding capacity and lower distortion than spatial domain histogram modification based schemes; and it achieved better performance than integer DCT (Discrete Cosine Transformation) based histogram modification scheme.

scholarly journals A Joint Encryption and Reversible Data Hiding Scheme Based on Integer-DWT and Arnold Map Permutation

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Shun Zhang ◽  
Tiegang Gao ◽  
Guorui Sheng
Keyword(s):  
Frequency Domain ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
Cover Image ◽  
Discrete Wavelet ◽  
Original Image ◽  
Histogram Modification ◽  
Encrypted Image ◽  
Hidden Data ◽  
Arnold Map

A joint encryption and reversible data hiding (joint encryption-RDH) scheme is proposed in this paper. The cover image is transformed to the frequency domain with integer discrete wavelet transform (integer DWT) for the encryption and data hiding. Additional data is hidden into the permuted middle (LH, HL) and high (HH) frequency subbands of integer DWT coefficients with a histogram modification based method. A combination of permutations both in the frequency domain and in the spatial domain is imposed for the encryption. In the receiving end, the encrypted image with hidden data can be decrypted to the image with hidden data, which is similar to the original image without hidden data, by only using the encryption key; if someone has both the data hiding key and the encryption key, he can both extract the hidden data and reversibly recover the original image. Experimental results demonstrate that, compared with existing joint encryption-RDH schemes, the proposed scheme has gained larger embedding capacity, and the distribution of the encrypted image with data hidden has a random like behavior. It can also achieve the lossless restoration of the cover image.

An Iterative Lifting Scheme on DCT Coefficients for Image Coding

2015 ◽  
Vol 3 (4) ◽  
pp. 317-319
Author(s):  
K. Sowmithri
Keyword(s):  
Image Coding ◽  
Signal To Noise Ratio ◽  
Image Data ◽  
Lifting Scheme ◽  
Discrete Wavelet ◽  
Jpeg 2000 ◽  
Scalar Quantization ◽  
Coding Schemes ◽  
Level Information ◽  
Dct Coefficients

Image coding is considered to be more effective, as it reduces number of bits required to store and/or to transmit image data. Transform based image coders play a significant role as they decorrelate the spatial low level information. It is found utilization in International compression standards such as JPEG, JPEG 2000, MPEG and H264. The choice of transform is an important issue in all these transforms coding schemes. Most of the literature suggests either Discrete Cosine Transform (DCT) or Discrete Wavelet Transform (DWT). In this proposed work, the energy preservation of DCT coefficients is analysed, and to down sample these coefficients, lifting scheme is iteratively applied so as to compensate the artifacts that appear in the reconstructed picture, and to yield the higher compression ratio. This is followed by scalar quantization and entropy coding, as in JPEG. The performance of the proposed iterative lifting scheme, employed on decorrelated DCT coefficients is measured with standard Peak Signal to Noise Ratio (PSNR) and the results are encouraging.

scholarly journals Digital Image Steganography Scheme Based on DWT and SVD

2020 ◽  
Vol 13 (4) ◽  
pp. 10-17
Author(s):  
Fadhil Kadhim Zaidan
Keyword(s):  
High Frequency ◽  
Signal To Noise Ratio ◽  
Similarity Index ◽  
Structural Similarity ◽  
Image Steganography ◽  
Discrete Wavelet ◽  
Grayscale Image ◽  
Structural Similarity Index ◽  
Value Decomposition ◽  
Index Measure

In this work, a grayscale image steganography scheme is proposed using a discrete wavelet transform (DWT) and singular value decomposition (SVD). In this scheme, 2-level DWT is applied to a cover image to obtain the high frequency band HL2 which is utilized to embed a secret grayscale image based on the SVD technique. The robustness and the imperceptibility of the proposed steganography algorithm are controlled by a scaling factor for obtaining an acceptable trade-off between them. Peak signal to noise ratio (PSNR) and Structural Similarity Index Measure (SSIM) are used for assessing the efficiency of the proposed approach. Experimental results demonstrate that the proposed scheme still holds its validity under different known attacks such as noise addition, filtering, cropping and JPEG compression

scholarly journals Audio Hiding based on Wavelet Transform and Linear Predictive Coding

2016 ◽  
Vol 42 (1) ◽  
pp. 30-37
Author(s):  
Jamal Hasoon ◽  
Saad Al-Saad
Keyword(s):  
Wavelet Transform ◽  
Efficient Method ◽  
High Frequency ◽  
Signal To Noise Ratio ◽  
Predictive Coding ◽  
Discrete Wavelet ◽  
Linear Predictive Coding ◽  
Signal To Noise ◽  
Log Likelihood ◽  
Objective Tests

In this work an efficient method for hiding a speech in audio is proposed. The features of secretspeech is extracted with LPC (Linear Predictive Coding), and these parameters embedded in audio inchaotic order. Discrete Wavelet Transform (DWT) is applied on audio frames to split the signal in high andlow frequencies. The embedding parameters are embedded in high frequency. The stego audio isperceptually indistinguishable from the equivalent cover audio. The proposed method allows hiding a sameduration of speech (secret) and audio (cover). The stego audio is subjected to objective tests such signal to noiseratio (SNR), signal to noise ratio segmental (SNRseg), Segmental Spectral SNR, Log Likelihood Ratio (LLR)and Correlation (Rxy) to determine the similarity with original audio.

scholarly journals AN ENHANCED IMAGE STEGANOGRAPHY TECHNIQUE FOR HIGH-SECURITY COMMUNICATION

2021 ◽  
Vol 9 (2) ◽  
pp. 1-6
Author(s):  
Apoorv Mahajan ◽  
Arpan Singh Rajput
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Data Hiding ◽  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Discrete Wavelet ◽  
Minimum Mean Squared Error ◽  
The Matrix ◽  
Value Decomposition

Purpose of the study: We propose an approach to hide data in an image with minimum Mean Squared Error (MSE) and maximum Signal-to-Noise ratio (SNR) using Discrete Wavelet Transform (DWT). Methodology: The methodology used by us considers the application of Discrete Wavelet transform to transform the values of the image into a different domain for embedding the information to be hidden in the image and then using Singular Value decomposition we decomposed the matrix values of the image for better data hiding. Main Findings: The application of the SVD function gave the model a better performance and also RED pixel values with the High-High frequency domain are a better cover for hiding data. Applications of this study: This article can be used for further research on applications of mathematical and frequency transformation functions on data hiding. It can also be used to implement a highly secure image steganography model. Novelty/Originality of this study: The application of Discrete Wavelet Transform has been used before but the application of SVD and hiding data in the H-H domain to obtain better results is original.

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