Reversible Information of Encrypted Image Based on Feature Difference Detection and Wavelet Transform

Aiming at the shortcomings of the existing lossless digital watermarking algorithm based on frequency domain in reversibility and embedding capacity, this study proposes a lossless digital image watermarking algorithm based on fractional wavelet transform, which is used for large-capacity reversible information hiding of images. First, the image is transformed by LeGall5/3 fractional wavelet, and then, the watermark is embedded in the high-frequency subband by the histogram shift method. In order to obtain maximum embedding capacity and reduce image distortion, the methods of selecting embedding parameters and stopping parameters are proposed, respectively. At the same time, in order to prevent overflow and reduce additional information, a new method of generating position map is proposed. The experimental results show that Lena is the result of multilayer embedding based on the algorithm in this study. In order to better observe the distortion phenomenon and enlarge the image, the Lena test image is the watermark image obtained after two and three layers of embedding, and its embedding capacity can be 2.7 bpp. It is proved that wavelet transform is suitable for encrypted images to implement covert communication.

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Image Watermarking pada Citra Medis menggunakan Compressive Sensing berbasis Stationary Wavelet Transform

ELKOMIKA Jurnal Teknik Energi Elektrik Teknik Telekomunikasi & Teknik Elektronika ◽

10.26760/elkomika.v8i1.43 ◽

2020 ◽

Vol 8 (1) ◽

pp. 43

Author(s):

YASQI HAFIZHANA ◽

IRMA SAFITRI ◽

LEDYA NOVAMIZANTI ◽

NUR IBRAHIM

Keyword(s):

Wavelet Transform ◽

Compressive Sensing ◽

Bit Error Rate ◽

Error Rate ◽

Image Watermarking ◽

Extraction Process ◽

Embedding Capacity ◽

Stationary Wavelet Transform ◽

Final Project ◽

Ownership Rights

ABSTRAK Watermarking pada citra medis dilakukan untuk melindungi hak kepemilikan dan keaslian sebuah citra medis. Proses embedding dan extraction dirancang menggunakan metode Stationary Wavelet Transform (SWT) dan Statistical Mean Manipulation (SMM) untuk mengubah citra host menjadi sinyal sparse kemudian memasuki proses watermarking. Citra watermark dioptimasi dengan menggunakan metode Compressive Sensing (CS). Hasil akhir dari penelitian ini menunjukkan simulasi Image Watermarking dengan Bit Error Rate (BER) mendekati nilai nol dan PSNR lebih besar dari 40 dB, tanpa diberikan serangan. Penerapan Compressive Sensing menyebabkan nilai PSNR meningkat hingga 3,5 dB dan embedding capacity menjadi empat kali lipat lebih baik. Kata Kunci: Image watermarking, Telemedicine, Stationary Wavelet Transform, Statistical Mean Manipulation, Compressive Sensing. ABSTRACT Watermarking in medical images is carried out to protect ownership rights and authenticity of a medical image. The embedding and extraction process was designed using Stationary wavelet transform (SWT) and Statistical Mean Manipulation (SMM) methods to convert the host image into a sparse signal and then enter the watermarking process. The watermark image is optimized using the Compressive Sensing (CS) method. The final result of this final project shows the simulation of Image Watermarking with the Bit Error Rate (BER) approaching zero and PSNR greater than 40 dB, without being given an attack. The application of the Compressive Sensing pursuit will cause the PSNR increase up to 3.5 dB and embedding capacity four times better. Keywords: Image watermarking, Telemedicine, Stationary Wavelet Transform, Statistical Mean Manipulation, Compressive Sensing.

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Reversible Information Hiding Algorithm Based on Multikey Encryption

Wireless Communications and Mobile Computing ◽

10.1155/2020/8847559 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10

Author(s):

Zhaohui Li ◽

Yiqing Wang ◽

Zhi Wang ◽

Zheli Liu ◽

Jian Zhang ◽

...

Keyword(s):

Spatial Correlation ◽

Data Hiding ◽

Information Hiding ◽

Reversible Data Hiding ◽

Rate Distortion ◽

Selection Method ◽

Original Image ◽

Embedding Capacity ◽

Reversible Information Hiding ◽

Encrypted Images

This paper proposes a scheme of reversible data hiding in encrypted images based on multikey encryption. There are only two parties that are involved in this framework, including the content owner and the recipient. The content owner encrypts the original image with a key set which is composed by a selection method according to the additional message. Thus, the image can be encrypted and embedded at the same time. Additional message can be extracted given that the recipient side could perform decryption strategy by exploiting spatial correlation; then, original image can be recovered without any loss. Compare with other current information hiding mechanism, the proposed approach provides higher embedding capacity and is also able to perfectly reconstruct the original image as well as the embedded message. Rate distortion of the proposed method outperforms the previously published ones.

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Compressive Sensing Audio Watermarking dengan Metode LWT dan QIM

ELKOMIKA Jurnal Teknik Energi Elektrik Teknik Telekomunikasi & Teknik Elektronika ◽

10.26760/elkomika.v6i3.405 ◽

2018 ◽

Vol 6 (3) ◽

pp. 405

Author(s):

IRMA SAFITRI ◽

NUR IBRAHIM ◽

HERLAMBANG YOGASWARA

Keyword(s):

Wavelet Transform ◽

Compressive Sensing ◽

Audio Watermarking ◽

Quantization Index Modulation ◽

Computationally Efficient ◽

Black And White ◽

Additional Information ◽

Audio Files ◽

Index Modulation ◽

Mp3 Compression

ABSTRAKPenelitian ini mengembangkan teknik Compressive Sensing (CS) untuk audio watermarking dengan metode Lifting Wavelet Transform (LWT) dan Quantization Index Modulation (QIM). LWT adalah salah satu teknik mendekomposisi sinyal menjadi 2 sub-band, yaitu sub-band low dan high. QIM adalah suatu metode yang efisien secara komputasi atau perhitungan watermarking dengan menggunakan informasi tambahan. Audio watermarking dilakukan menggunakan file audio dengan format *.wav berdurasi 10 detik dan menggunakan 4 genre musik, yaitu pop, classic, rock, dan metal. Watermark yang disisipkan berupa citra hitam putih dengan format *.bmp yang masing-masing berukuran 32x32 dan 64x64 pixel. Pengujian dilakukan dengan mengukur nilai SNR, ODG, BER, dan PSNR. Audio yang telah disisipkan watermark, diuji ketahanannya dengan diberikan 7 macam serangan berupa LPF, BPF, HPF, MP3 compression, noise, dan echo. Penelitian ini memiliki hasil optimal dengan nilai SNR 85,32 dB, ODG -8,34x10-11, BER 0, dan PSNR ∞.Kata kunci: Audio watermarking, QIM, LWT, Compressive Sensing. ABSTRACTThis research developed Compressive Sensing (CS) technique for audio watermarking using Wavelet Transform (LWT) and Quantization Index Modulation (QIM) methods. LWT is one technique to decompose the signal into 2 sub-bands, namely sub-band low and high. QIM is a computationally efficient method or watermarking calculation using additional information. Audio watermarking was done using audio files with *.wav format duration of 10 seconds and used 4 genres of music, namely pop, classic, rock, and metal. Watermark was inserted in the form of black and white image with *.bmp format each measuring 32x32 and 64x64 pixels. The test was done by measuring the value of SNR, ODG, BER, and PSNR. Audio that had been inserted watermark was tested its durability with given 7 kinds of attacks such as LPF, BPF, HPF, MP3 Compression, Noise, and Echo. This research had optimal result with SNR value of 85.32 dB, ODG value of -8.34x10-11, BER value of 0, and PSNR value of ∞.Keywords: Audio watermarking, QIM, LWT, Compressive Sensing.

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LWT-DCT based Image Watermarking Scheme using Normalized SVD

Recent Advances in Computer Science and Communications ◽

10.2174/2666255813999200821161656 ◽

2020 ◽

Vol 13 ◽

Author(s):

Rahul Dixit ◽

Amita Nandal ◽

Arvind Dhaka ◽

Vardan Agarwal ◽

Yohan Varghese

Keyword(s):

Wavelet Transform ◽

Singular Value Decomposition ◽

Discrete Cosine Transform ◽

Image Watermarking ◽

Singular Value ◽

Cover Image ◽

Lifting Wavelet Transform ◽

Cosine Transform ◽

Lifting Wavelet ◽

Value Decomposition

Background: Nowadays information security is one of the biggest issues of social networks. The multimedia data can be tampered with, and the attackers can then claim its ownership. Image watermarking is a technique that is used for copyright protection and authentication of multimedia. Objective: We aim to create a new and more robust image watermarking technique to prevent illegal copying, editing and distribution of media. Method : The watermarking technique proposed in this paper is non-blind and employs Lifting Wavelet Transform on the cover image to decompose the image into four coefficient matrices. Then Discrete Cosine Transform is applied which separates a selected coefficient matrix into different frequencies and later Singular Value Decomposition is applied. Singular Value Decomposition is also applied to the watermarking image and it is added to the singular matrix of the cover image which is then normalized followed by the inverse Singular Value Decomposition, inverse Discrete Cosine Transform and inverse Lifting Wavelet Transform respectively to obtain an embedded image. Normalization is proposed as an alternative to the traditional scaling factor. Results: Our technique is tested against attacks like rotation, resizing, cropping, noise addition and filtering. The performance comparison is evaluated based on Peak Signal to Noise Ratio, Structural Similarity Index Measure, and Normalized Cross-Correlation. Conclusion: The experimental results prove that the proposed method performs better than other state-of-the-art techniques and can be used to protect multimedia ownership.

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Image encryption based on Fractional wavelet transform, Arnold transform with the double random phases in HSV color domain

Recent Advances in Computer Science and Communications ◽

10.2174/2666255813999200918123535 ◽

2020 ◽

Vol 13 ◽

Author(s):

Aarushi Shrivastava ◽

Janki Ballabh Sharma ◽

Sunil Dutt Purohit

Keyword(s):

Wavelet Transform ◽

Image Encryption ◽

Fractional Fourier Transform ◽

Color Image ◽

Random Phase ◽

Arnold Transform ◽

Time Frequency ◽

Key Space ◽

Secret Keys ◽

Fractional Wavelet Transform

Objective: In the recent multimedia technology images play an integral role in communication. Here in this paper, we propose a new color image encryption method using FWT (Fractional Wavelet transform), double random phases and Arnold transform in HSV color domain. Methods: Firstly the image is changed into the HSV domain and the encoding is done using the FWT which is the combination of the fractional Fourier transform with wavelet transform and the two random phase masks are used in the double random phase encoding. In this one inverse DWT is taken at the end in order to obtain the encrypted image. To scramble the matrices the Arnold transform is used with different iterative values. The fractional order of FRFT, the wavelet family and the iterative numbers of Arnold transform are used as various secret keys in order to enhance the level of security of the proposed method. Results: The performance of the scheme is analyzed through its PSNR and SSIM values, key space, entropy, statistical analysis which demonstrates its effectiveness and feasibility of the proposed technique. Stimulation result verifies its robustness in comparison to nearby schemes. Conclusion: This method develops the better security, enlarged and sensitive key space with improved PSNR and SSIM. FWT reflecting time frequency information adds on to its flexibility with additional variables and making it more suitable for secure transmission.

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