HH Subband Research Articles

Analysis and effectiveness of deeper levels of SVD on performance of hybrid DWT and SVD watermarking

In this paper, an analysis on hybrid Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) for image watermarking is carried out to investigate the effect of a deeper level of the SVD on imperceptibility and robustness to resist common signal processing and geometric attacks. For this purpose, we have designed two hybrid watermarking schemes, the first one with DWT and first level of SVD, whereas, in the second scheme, the same design is employed with a second level of SVD. In this experiment, a comprehensive analysis is performed on the two designed schemes and the effect of robustness and imperceptibility is compared in the first and second levels of SVD in each DWT sub-band. Having analyzed more than 100 medical and non-medical images in standard datasets and real medical samples of patients, the experimental outcomes show a remarkable increase in both imperceptibility and robustness in the second level of SVD, in comparison to the first level. In addition, the achieved result shows that the SVD2 scheme offers the highest imperceptibility in the LL sub-band (more than 60 dB on average PSNR), with satisfactory robustness against noise attacks, but less persistence in some geometric attacks such as cropping. For the HH sub-band, strong robustness against all types of tested of attacks is obtained, though its imperceptibility is slightly lower than the achieved PSNR in the LL sub-band. In HH sub-band, an average growth of 5 dB in PSNR and 2% in NC can be observed from the second level of SVD in comparison to the first level. These results make SVD2 a good candidate for content protection, especially for medical images.

Noise Estimation and Type Identification in Natural Scene and Medical Images using Deep Learning Approaches

The image enhancement for the natural images is the vast field where the quality of the images degrades based on the capturing and processing methods employed by the capturing devices. Based on noise type and estimation of noise, filter need to be adopted for enhancing the quality of the image. In the same manner, the medical field also needs some filtering mechanism to reduce the noise and detection of the disease based on the clarity of the image captured; in accordance with it, the preprocessing steps play a vital role to reduce the burden on the radiologist to make the decision on presence of disease. Based on the estimated noise and its type, the filters are selected to delete the unwanted signals from the image. Hence, identifying noise types and denoising play an important role in image analysis. The proposed framework addresses the noise estimation and filtering process to obtain the enhanced images. This paper estimates and detects the noise types, namely Gaussian, motion artifacts, Poisson, salt-andpepper, and speckle noises. Noise is estimated by using discrete wavelet transformation (DWT). This separates the image into quadruple sub-bands. Noise and HH sub-band are high-frequency components. HH sub-band also has vertical edges. These vertical edges are removed by performing Hadamard operation on downsampled Sobel edge-detected image and HH sub-band. Using HH sub-band after removing vertical edges is considered for estimating the noise. The Rician energy equation is used to estimate the noise. This is given as input for Artificial Neural Network to improve the estimated noise level. For identifying noise type, CNN is used. After removing vertical edges, the HH sub-band is given to the CNN model for classification. The classification accuracy results of identifying noise type are 100% on natural images and 96.3% on medical images.

Reversible Video Steganography Using Quick Response Codes and Modified ElGamal Cryptosystem

The rapid transmission of multimedia information has been achieved mainly by recent advancements in the Internet's speed and information technology. In spite of this, advancements in technology have resulted in breaches of privacy and data security. When it comes to protecting private information in today's Internet era, digital steganography is vital. Many academics are interested in digital video because it has a great capability for concealing important data. There have been a vast number of video steganography solutions developed lately to guard against the theft of confidential data. The visual imperceptibility, robustness, and embedding capacity of these approaches are all challenges that must be addressed. In this paper, a novel solution to reversible video steganography based on Discrete Wavelet Transform (DWT) and Quick Response (QR) codes is proposed to address these concerns. In order to increase the security level of the suggested method, an enhanced ElGamal cryptosystem has also been proposed. Prior to the embedding stage, the suggested method uses the modified ElGamal algorithm to encrypt secret QR codes. Concurrently, it applies two-dimensional DWT on the Y-component of each video frame resulting in Approximation (LL), Horizontal (LH), Vertical (HL), and Diagonal (HH) sub-bands. Then, the encrypted Low (L), Medium (M), Quantile (Q), and High (H) QR codes are embedded into the HL sub-band, HH sub-band, U-component, and V-component of video frames, respectively, using the Least Significant Bit (LSB) technique. As a consequence of extensive testing of the approach, it was shown to be very secure and highly invisible, as well as highly resistant to attacks from Salt & Pepper, Gaussian, Poisson, and Speckle noises, which has an average Structural Similarity Index (SSIM) of more than 0.91. Aside from visual imperceptibility, the suggested method exceeds current methods in terms of Peak Signal-to-Noise Ratio (PSNR) average of 52.143 dB, and embedding capacity 1 bpp.

Bit Plane Slicing based Digital Watermarking Technique in DWT Domain

Authenticity of image and its copyright protection are one of the essential application of watermarking. In this paper, a hybrid technique for watermarking in DWT domain is presented for its application in the field of providing authentication to images. In this work binary image is used as watermark and is embedded in the 'host image'. Before embedding the watermark in the host, the host image is splitted into 8 bit planes using bit plane slicing. Followed that DWT is applied to the least significant bit plane which partitions the respective plane into low frequency (LL subband) and high frequency (HH, HL and LH subbands). The SVD is applied to HH subband of least significant bit plane and watermark is embedded on the singular matrix part of SVD. To analyse the robustness of the scheme proposed in this paper, watermarked image is attacked by different image processing attacks. Original watermark and extracted watermark is compared on the scale of normalized correlation to measure the robustness of the scheme against various attacks.

Imperceptible Improvement of Secure Image Steganography based on Wavelet Transform and OTP Encryption using PN Generator

Digital data is widely transacted through internet media that can be accessed publicly, so this requires security of the data. This research proposes a combination of steganography and cryptography methods using wavelet transforms and OTP encryption based on PN generators. The PN generator is used as a tool to generate binary random numbers that are used to improve the quality of the embedding process and the encryption process. Messaging is carried out with four levels of wavelet transformation, the first three levels of the LL subband are selected to be transformed, while the fourth level wavelet transformation is selected for the HH subband to be embedded. This subband selection strategy is carried out with the aim of getting good imperceptibility and robust values. While OTP encryption is proposed because it has strong encryption results with a lightweight computing process. Based on the experimental results, binary random numbers generated by PN generators have been proven to successfully improve the quality of stego images and security. This has been measured by the PSNR and MSE, where there are remembrances on the two measuring instruments.

Adaptive Generalized Gaussian Distribution Oriented Thresholding Function for Image De-Noising

In this paper, an Adaptive Generalized Gaussian Distribution (AGGD) oriented thresholding function for image de-noising is proposed. This technique utilizes a unique threshold function derived from the generalized Gaussian function obtained from the HH sub-band in the wavelet domain. Two-dimensional discrete wavelet transform is used to generate the decomposition. Having the threshold function formed by using the distribution of the high frequency wavelet HH coefficients makes the function data dependent, hence adaptive to the input image to be de-noised. Thresholding is performed in the high frequency sub-bands of the wavelet transform in the interval [-t, t], where t is calculated in terms of the standard deviation of the coefficients in the HH sub-band. After thresholding, inverse wavelet transform is applied to generate the final de-noised image. Experimental results show the superiority of the proposed technique over other alternative state-of-the-art methods in the literature.

A multiplicative video watermarking robust to H.264/AVC compression standard

The widespread application of the H.264 video compression standard necessitates proper design of copyright protection algorithms. In this paper, a new blind multiplicative video watermarking algorithm robust to this standard and also other attacks is proposed. With this method, the multiplicative watermark is embedded in the HH subband of the wavelet-transformed video frames. The HH coefficients of the host signal are divided into two patches: One patch is used to host the watermark, while the other patch is remained intact to be exploited at the receiver for estimating the system parameters required for watermark detection. Assuming the wavelet HH coefficients to have the Laplacian distribution, the maximum likelihood (ML) criterion is used for the watermark detection. In this case, the ratio of summation of samples of two patches is used as our decision variable on which the ML criterion is applied. Simulation results show that along with the exhibition of an acceptable robustness against various attacks, the proposed algorithm properly satisfies the invisibility requirements of the watermarking concept with low computational complexity.

A DWT-SVD based multiple watermarking scheme for image based data security

In this paper a novel image based data security and authentication based, image watermarking scheme that combines the discrete wavelet transform (DWT) and Singular value decomposition (SVD) is proposed. This paper explains a dual watermarking scheme with different algorithm. At first original image is divided into its appropriate levels by using DWT, and convert LL sub-band to its red, green and blue component, and the obtained colour component of image is divided into non-overlapping blocks, final apply SVD on each block to obtained the singular value for watermarking. The second scheme chose HH sub-band of original image and converts its own red, green, blue component, and then apply SVD to each colour component to obtain the singular value for watermarking. We take two watermark images one is Logo image and other is Quick Response Code (QR Code) for experiment. Results obtained from the experiment reflect the efficiency of the proposed scheme.

A robust video watermarking algorithm based on chaotic maps and discrete wavelet transform

Abstract. In this paper, we present a video watermarking scheme based on chaotic maps in wavelet domain. The embedding procedure is done before video compression stage. At first, we encrypt the watermark signal by a Tent map, next the encrypted watermark is embedded in HH sub-band coefficients of I-frames. This task will increase the security and resistance of our watermarking system. Experimental results verify the resistance of our proposed method against signal processing and geometric attacks. We also comprise the efficiency of our algorithm against some other methods. Comparison results show the superiority of our scheme against others.

Blind and Robust Images Watermarking Based on Wavelet and Edge Insertion

This paper gives a new scheme of watermarking technique related to insert the mark by adding edge in HH sub-band of the host image after wavelet decomposition. Contrary to most of the watermarking algorithms in wavelet domain, our method is blind and results show that it is robust against the JPEG and GIF compression, histogram and spectrum spreading, noise adding and small rotation. Its robustness against compression is better than others watermarking algorithms reported in the literature. The algorithm is flexible because its capacity or robustness can be improved by modifying some parameters.

De-speckling 2D-Discrete Wavelet Transform with Hard Threshold Stage

In this work, a new method is implemented for removing noise from gray scale image that depends on two-dimensional discrete wavelet transform and Threshold stage (hard threshold). This paper represents the algorithm to remove the speckle noise by using logarithm operation. This operation changes the multiplicative noise to additive noise. So that, the removing operation becomes easier. The Matlab program is used to build the Algorithm and measure the PSNR and other measurement criteria as (NMV, NV, NSD, ENL and PSNR) to study the effect of removing noise from corrupted image. The PSNR reaches to 24dB which is very satisfactory result in the reconstructed image, while the maximum value of ENL is 2.23 * 106, and the minimum value of NMV, NV, NSD which is equal to 6.79, 2.67*10-5, 46* 10-4 respectively gives a smoother and cleaner image. The universal Threshold is applied in high frequency coefficient (i.e. the LH, HL, and HH-sub band of image) to remove the speckle noise and the low frequency coefficient (LL-sub band of image) is still without any change.

A NOVEL DIGITAL IMAGE WATERMARKING SCHEME USING BIORTHOGONAL WAVELETS

Copyright protection is considered as an issue of vital significance owing to the escalating utilization of internet and effortless copying, tampering and distribution of digital images. Digital watermarking methodologies are looked upon as a competent tool for safeguarding the digital images from copyright infringements issues. A number of researches in existence deal with copyright protection with the aid of watermarking. Recently, wavelet domain based watermarking approaches are gaining popularity in watermarking researches. In this paper we have proposed a novel watermarking scheme for copyright protection in digital images. The watermarking is performed in wavelet domain using bi-orthogonal wavelet transform. As the proposed approach is non-blind, it requires original image for extracting the watermark. The watermark image is a binary image. The watermark image is embedded in the HH sub-band of the wavelet transformed original image. A Good quality of watermarked image is assured through the proposed scheme from the higher PSNR values which is evident from experimental result.

A Fragile Watermarking Scheme for Image Authentication with Tamper Localization Using Integer Wavelet Transform

Problem statement: In recent years, as digital media are gaining wider popularity, their security related issues are becoming greater concern. Method for authenticating and assuring the integrity of the image is required. Image authentication is possible by embedding a layer of the authentication signature into the digital image using a digital watermark. In some applications tamper localization is also required. Approach: In this study, we proposed a fragile image authentication system with tamper localization in wavelet domain. In this scheme, secret data to be embedded is a logo. Watermark was generated by repeating logo image so that size of watermark matches with the size of HH sub-band of integer wavelet transform. To provide additional level of security, the generated watermark was scrambled using a shared secret key. Integer Haar wavelet transform was applied to obtain wavelet coefficients. Watermark was embedded into the coefficients using odd-even mapping. Results: Experimental results demonstrated that proposed scheme detected and localized tampering at pixel level. Proposed scheme was tested with images of various sizes and tampering of various sizes. It provided good results for tamperings ranges from single pixel to a block of pixels. Conclusion: Watermarking was done in wavelet domain; conventional watermarking attacks were not possible. The resolution of tamper localization was achieved at pixel level. The watermarked image's quality was still maintained while providing pixel-level tampering accuracy. Proposed scheme can be used in insurance, forensics departments.