scholarly journals Digital Watermarking for Image Authentication using Spatial-Scale Domain based Techniques

2019 ◽  
Vol 8 (4) ◽  
pp. 2334-2341
Keyword(s):  
Wavelet Transform ◽  
Spatial Scale ◽  
Digital Watermarking ◽  
Image Watermarking ◽  
Similarity Index ◽  
Structural Similarity ◽  
Image Authentication ◽  
Objective Evaluation ◽  
Contourlet Transform ◽  
Discrete Wavelet

This paper aims in presenting a thorough comparison of performance and usefulness of concept of spatial-scale domain based techniques in digital watermarking in order to sustain the ownership, security and true authentication. Spatial-scale based image watermarking techniques provides the information of 2-Dimensional (2-D) signal at different scales and levels, which is desirable for image watermarking. Further, these techniques emerged as a powerful and efficient tool to overcome the limitation of Fourier, spatial, as well as, purely frequency based techniques. The spatial-scale based watermarking techniques, namely, Contourlet Transform (CT), Non Sub-sampled Contourlet Transform (NSCT), Stationary Wavelet Transform (SWT) and Discrete Wavelet Transform (DWT) have been selected for watermarking process. Further, the comparison of performance of the selected watermarking techniques have been carried out in terms of different metrics, such as Peak Signal-to-Noise Ratio (PSNR), Root Mean Square Error (RMSE), Tamper Assessment Factor (TAF) and Mean Structural Similarity Index (MSSIM). Analysis of result shows that multi-directional and shift-invariant NSCT technique outperforms the SWT and DWT based image watermarking techniques in terms of authentication, better capture quality, and tampering resistance, subjective and objective evaluation.

scholarly journals Encryption Based Image Watermarking Algorithm in 2DWT-DCT Domains

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5540
Author(s):  
Nayeem Hasan ◽  
Md Saiful Islam ◽  
Wenyu Chen ◽  
Muhammad Ashad Kabir ◽  
Saad Al-Ahmadi
Keyword(s):  
Signal To Noise Ratio ◽  
Image Watermarking ◽  
Similarity Index ◽  
Structural Similarity ◽  
Reconstructed Image ◽  
Discrete Wavelet ◽  
Signal To Noise ◽  
Noise Ratio ◽  
Watermarking Scheme

This paper proposes an encryption-based image watermarking scheme using a combination of second-level discrete wavelet transform (2DWT) and discrete cosine transform (DCT) with an auto extraction feature. The 2DWT has been selected based on the analysis of the trade-off between imperceptibility of the watermark and embedding capacity at various levels of decomposition. DCT operation is applied to the selected area to gather the image coefficients into a single vector using a zig-zig operation. We have utilized the same random bit sequence as the watermark and seed for the embedding zone coefficient. The quality of the reconstructed image was measured according to bit correction rate, peak signal-to-noise ratio (PSNR), and similarity index. Experimental results demonstrated that the proposed scheme is highly robust under different types of image-processing attacks. Several image attacks, e.g., JPEG compression, filtering, noise addition, cropping, sharpening, and bit-plane removal, were examined on watermarked images, and the results of our proposed method outstripped existing methods, especially in terms of the bit correction ratio (100%), which is a measure of bit restoration. The results were also highly satisfactory in terms of the quality of the reconstructed image, which demonstrated high imperceptibility in terms of peak signal-to-noise ratio (PSNR ≥ 40 dB) and structural similarity (SSIM ≥ 0.9) under different image attacks.

scholarly journals A Watermarking Method for Selective Image Authentication Tollerant to JPEG Compression, Brightness and Contrast Adjustments

2020 ◽  
Vol 6 (3) ◽  
pp. 92-99
Author(s):  
A. Zhuvikin
Keyword(s):  
Wavelet Transform ◽  
Digital Watermarking ◽  
Visual Quality ◽  
Image Authentication ◽  
Jpeg Compression ◽  
Discrete Wavelet ◽  
Embedding Capacity ◽  
Image Histogram ◽  
Embedding Technique ◽  
Promising Application

One of the most promising application of the digital watermarking is the selective image authentication (SIA) systems. In order to implement such a system one requires an embedding algorithm with an appropriate capacity. In addition, an embedding method is to be robust for the class of non-malicious manipulations which the SIA system is designed for. We propose the new method which has a significant embedding capacity while still being tolerant to JPEG compression, brightness and contrast adjustments. This was possible due to the extension of the well-known discrete wavelet transform embedding technique. We propose two-step embedding scheme and the use of image histogram equalisation and recovering operations. The experiment results show acceptable tolerance to JPEG compression, brightness and contrast adjustments with good visual quality in terms of PSNR just after embedding.

scholarly journals Implementation of Spatial-Scale Domain Based De-Noising Techniques using Different Thresholding

2020 ◽  
Vol 9 (3) ◽  
pp. 3594-3603
Keyword(s):  
Wavelet Transform ◽  
Root Mean Square Error ◽  
Signal To Noise Ratio ◽  
Objective Evaluation ◽  
Contourlet Transform ◽  
Discrete Wavelet ◽  
Mean Square ◽  
Stationary Wavelet Transform ◽  
Signal To Noise ◽  
Different Levels

This paper aims in presenting a thorough comparison of performance and usefulness of multi-resolution based de-noising technique. Multi-resolution based image denoising techniques overcome the limitation of Fourier, spatial, as well as, purely frequency based techniques, as it provides the information of 2-Dimensional (2-D) signal at different levels and scales, which is desirable for image de-noising. The multiresolution based de-noising techniques, namely, Contourlet Transform (CT), Non Sub-sampled Contourlet Transform (NSCT), Stationary Wavelet Transform (SWT) and Discrete Wavelet Transform (DWT), have been selected for the de-noising of camera images. Further, the performance of different denosing techniques have been compared in terms of different noise variances, thresholding techniques and by using well defined metrics, such as Peak Signal-to-Noise Ratio (PSNR) and Root Mean Square Error (RMSE). Analysis of result shows that shift-invariant NSCT technique outperforms the CT, SWT and DWT based de-noising techniques in terms of qualititaive and quantitative objective evaluation

scholarly journals Image Watermarking Based on IWT and Parity Bit Checking

2021 ◽  
pp. 2726-2739
Author(s):  
Jalal H. Awad ◽  
Balsam D. Majeed
Keyword(s):  
Wavelet Transform ◽  
Image Quality ◽  
Signal To Noise Ratio ◽  
Image Watermarking ◽  
Similarity Index ◽  
Structural Similarity ◽  
Floating Point ◽  
Integer Coefficient ◽  
Authentication Mechanism ◽  
Image Pixels

     Various document types play an influential role in a lot of our lives activities today; hence preserving their integrity is an important matter. Such documents have various forms, including texts, videos, sounds, and images.  The latter types' authentication will be our concern here in this paper. Images can be handled spatially by doing the proper modification directly on their pixel values or spectrally through conducting some adjustments to some of the addressed coefficients. Due to spectral (frequency) domain flexibility in handling data, the domain coefficients are utilized for the watermark embedding purpose. The integer wavelet transform (IWT), which is a wavelet transform based on the lifting scheme, is adopted in this paper in order to provide a direct way for converting image pixels' integer values to integer coefficient values rather than floating point coefficients that could be produced by the traditional wavelet transform. This direct relation can enhance the processed image quality due to avoiding the rounding operations on the floating point coefficients. The well-known parity bit approach is also utilized in this paper as an authentication mechanism, where 3 secret parity bits are used for each block in an image which is divided into non-overlapped blocks in order to enforce a form of fragile watermark approach. Thus, any alteration in the block pixels could cause the adopted (even) parity to be violated. The fragile watermarking is achieved through the modification of least significant bits ((LSBs) of certain frequency coefficients' according to the even parity condition. In spite of this image watermarking operation, the proposed method is efficient. In order to prove the efficiency of our proposed method, it was tested against standard images using measurements like peak signal to noise ratio (PSNR) and structural similarity index (SSIM).  Experiments showed promising results; the method preserves high image quality (PSNR≈ 44.4367dB, SSIM≈ 0.9956) and good tamper detection capability.

An Efficient Discrete Wavelet Transform Based Hybrid Image Watermarking Algorithm Using Human Visual Model

2021 ◽  
Author(s):  
Sundhararaj V ◽  
Meenakshipriya B ◽  
Nirmala Devi P
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Image Watermarking ◽  
Similarity Index ◽  
Input Image ◽  
Digital Data ◽  
Discrete Wavelet ◽  
Weight Factor ◽  
Visual Model ◽  
Human Visual Model

Abstract More than ever with growing of multimedia technology, the digital data are exchanged in the internet, which can be duplicated by unauthorized users. To avoid this problem the watermarking technology has brought this paper. Performance improvement with compare to existing algorithm is obtained by proposing a new watermarking algorithm based on Human Visual Model (HVM) and Discrete Wavelet Transform (DWT) for securing the digital data and copyright protection. DWT is applied to the input image and at each level of DWT sub bands to embed a watermark image in selected coefficients of the sub band. HVM integrate the weight factor effect of human visualization by considering into the eye’s vision is less sensitivity area, depending on brightness, frequency band and texture areas of the image sub band. In the proposed approach robustly and imperceptibly, DWT and HVM are used for obtainable weight factor, according to human eye perceptual and to determine the optimal strength at which the threshold to embedding reaches the perceptual invisibility of watermarked image to various attacks. Performance is evaluated such as Peak Signal to Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM) and Quality Index (QI) is used to evaluate and achieve the imperceptible watermarked image. Results of PSNR values of hybrid image watermarking are between 49.73db to 36.24db. Experimental results show that our hybrid image watermarking process has enhanced robustness and displays the effectiveness of presenting images watermarking system.

Digital Watermarking Based on Wavelet and Chaotic Mapping

2014 ◽  
Vol 519-520 ◽  
pp. 520-523
Author(s):  
Yuan Song ◽  
Bo Zhou ◽  
Guo Jun Zhou
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Digital Watermarking ◽  
Frequency Band ◽  
Image Watermarking ◽  
Chaotic Sequence ◽  
Experimental Results ◽  
Discrete Wavelet ◽  
Original Image ◽  
Chaotic Mapping

An algorithm of wavelet digital watermarking was proposed to improve the security of the watermark. First, the logistic chaotic sequence was used to generate an encrypted image watermarking, then discrete wavelet transform (DWT) was used to decompose the original image and the watermark was embedded into the selected frequency band of significant wavelet coefficients. Finally, an approach for extraction was adopted. Experimental results show that the watermark is robust to attacks if the chaotic key is unknown.

scholarly journals Stationary Wavelet Transform based Radiometric Error Correction Technique for NOAA-AVHRR sensor data

2018 ◽  
Vol 7 (2.15) ◽  
pp. 177 ◽  
Author(s):  
V Raja Rajeswari ◽  
S Narayana Reddy ◽  
P Jagadamba
Keyword(s):  
Remote Sensing ◽  
Wavelet Transform ◽  
Median Filter ◽  
Similarity Index ◽  
Structural Similarity ◽  
Sensor Data ◽  
Discrete Wavelet ◽  
Stationary Wavelet Transform ◽  
Noaa Avhrr ◽  
Correction Technique

Due to the inaccuracy of the sensing devices remote sensing images contain radiometric errors, which can be severe in many cases. Therefore, the preprocessing is an inevitable step in the remote sensing image analysis. This paper presents radiometric errors and evaluates methodologies to retrieve information contained in images by means of filtering in the spatial domain and wavelet domain. Among those, the wavelet techniques are more effective to reduce noise because of their ability to capture the energy of a signal in fewer wavelet coefficients. In this study, Stationary Wavelet Transform (SWT) method and its application to NOAA -18, 19AVHRR/3 channel 3 and channel 4 images to correct radiometric error is presented. Qualitative and quantitative analysis was carried to evaluate the performance of SWT method, both by measuring the Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM), mean value, standard deviation and by visual inspection. The SWT based method can remove radiometric error effectively and preserves radiometric information to a desirable amount. From the results, SWT based method is better in smoothness and accuracy than the conventional mean filter, median filter and Discrete Wavelet Transform (DWT) based method  

scholarly journals A Watermarking Technique for Biomedical Images Using SMQT, Otsu, and Fuzzy C-Means

Electronics ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 975 ◽  
Author(s):  
Shaekh Hasan Shoron ◽  
Monamy Islam ◽  
Jia Uddin ◽  
Dongkoo Shon ◽  
Kichang Im ◽  
...  
Keyword(s):  
Digital Watermarking ◽  
Signal To Noise Ratio ◽  
Similarity Index ◽  
Structural Similarity ◽  
Threshold Value ◽  
Discrete Wavelet ◽  
Biomedical Images ◽  
Fuzzy C Means ◽  
Biomedical Image ◽  
Watermarking Scheme

Digital watermarking is a process of giving security from unauthorized use. To protect the data from any kind of misuse while transferring, digital watermarking is the most popular authentication technique. This paper proposes a novel digital watermarking scheme for biomedical images. In the model, initially, the biomedical image is preprocessed using improved successive mean quantization transform (SMQT) which uses the Otsu’s threshold value. In the next phase, the image is segmented using Otsu and Fuzzy c-means. Afterwards, the watermark is embedded in the image using discrete wavelet transform (DWT) and inverse DWT (IDWT). Finally, the watermark is extracted from the biomedical image by executing the inverse operation of the embedding process. Experimental results exhibit that the proposed digital watermarking scheme outperforms the typical models in terms of effectiveness and imperceptibility while maintaining robustness against different attacks by demonstrating a lower bit error rate (BER), a cross-correlation value closer to one, and higher values of structural similarity index measures (SSIM) and peak signal-to-noise ratio (PSNR).

Evaluating Multiscale Transform Based Image Compression Using Encoding Techniques

2016 ◽  
Vol 16 (04) ◽  
pp. 1650018
Author(s):  
S. P. Raja ◽  
A. Suruliandi
Keyword(s):  
Wavelet Transform ◽  
Image Compression ◽  
Signal To Noise Ratio ◽  
Similarity Index ◽  
Curvelet Transform ◽  
Structural Similarity ◽  
Contourlet Transform ◽  
Good Tool ◽  
Ridgelet Transform ◽  
Multiscale Transform

Image compression is the emerging field to transmit the multimedia products like image, video and audio. Image compression is used to reduce the storage quantity as much as possible. The objective of this paper is to compare the multiscale transform based image compression encoding techniques. The multiscale transforms involved in this paper are wavelet transform, bandelet transform, curvelet transform, ridgelet transform and contourlet transform. Wavelet transform allows good localization both in time and frequency domain. Bandelet transform takes geometric regularity of the natural images to improve the efficiency of representation. Curvelet transform handles curve discontinuities well. Curvelets are the good tool for the analysis and the computation of partial differential equations. Curvelets also have micro local features which make them especially adapted to certain reconstruction problems with missing data. The ridgelet transform is the core idea behind curvelet transform. It is used to represent objects with line singularities. The contourlet transform gets smooth contours and edges at any orientation. It filters noise as well. The Encoding techniques involved in this paper are spatial orientation tree wavelet (STW), set partitioned embedded block (SPECK) and compression with reversible embedded wavelet (CREW). The performance parameters such as peak signal to noise ratio (PSNR), image quality index and structural similarity index (SSIM) are used for the purpose of evaluation. It is found that bandelet transform with all the encoding techniques work well.

An Efficient Digital Watermarking Technique for Color Images Using Directional Transforms

2017 ◽  
Vol 3 (2) ◽  
pp. 1
Author(s):  
Nguyen Chi Sy ◽  
Ha Hoang Kha ◽  
Nguyen Minh Hoang
Keyword(s):  
Wavelet Transform ◽  
Digital Watermarking ◽  
Performance Metrics ◽  
Signal To Noise Ratio ◽  
Structural Similarity ◽  
Color Images ◽  
The Other ◽  
Discrete Wavelet ◽  
Signal To Noise ◽  
Transform Domains

This paper is concerned with a digital watermarking technique for color images based on directional transforms. Different from the traditional watermarking schemes which embed the watermarks into the spatial domain or frequency domain of the Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT), this paper investigates the performance of the watermarking schemes using the Fast Discrete Curvelet Transforms (FDCT) and Contourlet Transform (CT). We evaluate the performance of the watermarking schemes using the directional transforms on a standard database of color images in terms of invisibility and robustness. The performance metrics are measured by Peak Signal-to-Noise Ratio (PSNR), Normalized Correlation (NC), Structural SIMilarity (SSIM) and required time for extracting and embedding process. The experimental results reveal that watermarking schemes in the directional transform domains outperform the other schemes in DWT domains.

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