LH Subband Research Articles

Stegano-Purge: An integer wavelet transformation based adaptive universal image sterilizer for steganography removal

Sterilization is the method of annihilating steganographic data hidden in a cover media. This paper proposes a visual quality preserving image sterilization method that effectively modifies stego-data embedded by various steganography algorithms on random greyscale images. The method applies one-level Integer Wavelet Transform (IWT) on a suspected stego image to produce HH, HL, LH and LL sub-bands. The value of a sub-band coefficient is modified according to its agitation quotient. The coefficient agitation is computed using the proposed metric Unnormalized Hellinger Distance (UHD) between a specific sub-band coefficient and its neighbours. To mitigate the issue of variable noise tolerance of IWT sub-bands, the proposed method performs parameter-controlled adaptive modification. Purification of up to 3 bits is done in the most noise-resilient HH channel and up to 2 bits in moderately noise-sensitive HL and LH channels. The highly noise-susceptible LL channel is sterilized by adaptive bit-flipping. A parameter control algorithm balances the amount of channel-wise bit modification to optimize the visual quality. The stego images for evaluation have been prepared by applying eleven state-of-the-art steganography methods including UNIWARD and HUGO on benchmark datasets of USC-SIPI and BossBase 1.01. The proposed method achieves improved performance in comparison with the state-of-the-art sterilization techniques in terms of the visual quality of sterilized image, embedding scheme-wise percentage of sterilization and the sterilization time.

Aluminum-Copper alloys, Corrosion, acidic medium, alkali medium.

This paper suggested a de-noising algorithm used in grayscale images. As long as the noisy image does not give the desired view of its features, de-noising is required. The algorithm is based on block matching and wavelet transformation. Euclidean distance for blocks similarity is exploited, which demonstrate more accurate in finding similar blocks depending on soft thresholding. Regarding wavelet transform, a combine of hard thresholding is performed for HH and LH sub-bands while soft thresholding is used in LL and HL sub-bands of the decomposed images. Three types of noise is encountered: Gaussian noise, salt & pepper noise and speckle noise. The measurements are employed to evaluate our work is MSE and PSNR and SSIM. Finally a comparison of the results shows that our method outperforms traditional wavelet using hard or soft thresholding.

A New Robust and Secure 3-Level Digital Image Watermarking Method Based on G-BAT Hybrid Optimization

This contribution applies tools from the information theory and soft computing (SC) paradigms to the embedding and extraction of watermarks in aerial remote sensing (RS) images to protect copyright. By the time 5G came along, Internet usage had already grown exponentially. Regarding copyright protection, the most important responsibility of the digital image watermarking (DIW) approach is to provide authentication and security for digital content. In this paper, our main goal is to provide authentication and security to aerial RS images transmitted over the Internet by the proposal of a hybrid approach using both the redundant discrete wavelet transform (RDWT) and the singular value decomposition (SVD) schemes for DIW. Specifically, SC is adopted in this work for the numerical optimization of critical parameters. Moreover, 1-level RDWT and SVD are applied on digital cover image and singular matrices of LH and HL sub-bands are selected for watermark embedding. Further selected singular matrices SLH and SHL are split into 3×3 non-overlapping blocks, and diagonal positions are used for watermark embedding. Three-level symmetric encryption with low computational cost is used to ensure higher watermark security. A hybrid grasshopper–BAT (G-BAT) SC-based optimization algorithm is also proposed in order to achieve high quality DIW outcomes, and a broad comparison against other methods in the state-of-the-art is provided. The experimental results have demonstrated that our proposal provides high levels of imperceptibility, robustness, embedding capacity and security when dealing with DIW of aerial RS images, even higher than the state-of-the-art methods.

Image Interpolation Based on 2D-DWT with Novel Regularity-Preserving Algorithm Using RLS Adaptive Filters

This paper proposes a novel method for the image interpolation problem based on two-dimensional discrete wavelet transform (DWT) with the edge preserving approach. The purpose of this method is to consider two contrasting issues of over-smoothing and creation of spurious edges at the same time, and offer a novel solution based on statistical dependencies of image sub-bands, and noise behavior. The offered method has a multi-faceted approach for the problem; by sub-band coding, it handles each 2D-DWT image sub-band with a different solution. For LH and HL sub-bands, two algorithms work together in order to preserve regularity. Area_Check algorithm is a four-phase edge-preserving algorithm that aims to recognize and interpolate separating lines of environments and edgy regions in the best possible way. On the other hand, RLS_AVG algorithm interpolates smooth surfaces of the image by keeping the regularity of the image without over-smoothing. In this regard, the offered algorithm has a great power to counter jaggies and annoying artifacts. In the end, in order to demonstrate the capability, and performance of the proposed method, the final results in various metrics are compared with the results of the most famous and the newest image interpolation methods.

Watermarking berbasis Redundant Discrete Wavelet Transform dan Arnold Transform pada Citra Medis

In telemedicine, data transmission in digital medical images and electronic medical records through the internet is vulnerable to various threats of theft and manipulation. Image watermarking is needed to provide authentication and security to medical images. This paper proposes an image watermarking scheme based on Redundant Discrete Wavelet Transform (RDWT) and Discrete Cosine Transform (DCT) with watermark encryption using Arnold transform. First, the original host medical image was decomposed into four subbands using RDWT. Then, DCT is applied to the LH subband of the RDWT. On the other hand, the watermark is scrambled using Arnold transform to ensure identity security. The singular value of the watermarked image is obtained by modifying the singular value of the host image and the watermark. Tests were carried out on different medical images, namely X-ray, MRI, CT, and ultrasound, with a watermark in a proprietary logo. The host medical image is the same size as the watermark image. The result of this study can provide high authentication, imperceptibility and security in medical images, with an average PSNR value of 65.67 dB, SSIM 1, BER 0, NC 1. This scheme is resistant to JPEG compression, noise addition, filtering, image sharpening, image enhancement, geometric operations, motion blur, image sharpening, and histogram equalization.

A no-reference metric to assess quality of denoising for Magnetic Resonance images

Performance evaluation of algorithms used for denoising real-time Magnetic Resonance (MR) images and the selection of their operational parameters are difficult as noise-free ground-truth is unavailable. No-reference metrics that can reflect the quality of denoised images with respect to the strength of residual noise and inadvertent blur at edges are required in this context. A no-reference metric, termed as Objective Measure of Quality of Denoised Images (OMQDI), for assessing the quality of denoised MR images is proposed in this paper. OMQDI is a sum of two quality factors termed as Edge-Preservation Factor (EPF) and Noise Suppression Factor (NSF). EPF is computed from the sharpness of edges in the noisy input and denoised images and NSF is computed from the noise power in them. The sharpness is computed in the Wavelet domain. The sharpness is the nonlinearly weighted sum of cumulative log-energy of wavelet coefficients from three different levels of decomposition. Cumulative log-energy at any particular level of decomposition is computed from log-energy from LH, HL and HH sub-bands corresponding to that level of decomposition. The noise power is estimated from the global mean of local grey level variance with the help of a non-parametric model. The Pearson’s correlation with the subjective quality rating exhibited by No-Reference Structure Similarity (NRSS), Sparsity and Dominant orientation-based Quality Index (SDQI), MetricQ, Anisotropic Quality Index (AQI), Optimum Denoising Index (ODI) and OMQDI on 100 test datasets are 0.245 ± 0.1032, 0.5757 ± 0.2735, 0.5615 ± 0.2959, 0.6566 ± 0.2361, 0.8391 ± 0.085 and 0.9619 ± 0.0293, respectively. The computational time (in sec) of NRSS, SDQI, MetricQ, AQI, ODI and OMQDI are 0.0777 ± 0.0032, 0.1998 ± 0.1155, 2.4347 ± 0.0757, 5.4859 ± 1.4862, 0.2914 ± 0.0508 and 0.1382 ± 0.0164, respectively. OMQDI has good agreement with the subjective quality rating and it is fast in computation.

Robust watermarking scheme based LWT and SVD using artificial bee colony optimization

<span>This paper presents a watermarking scheme for grayscale images, in which lifting wavelet transform and singular value decomposition are exploited based on multi-objective artificial bee colony optimization to produce a robust watermarking method. Furthermore, for increasing security encryption of the watermark is done prior to the embedding operation. In the proposed scheme, the actual image is altered to four sub-band over three levels of lifting wavelet transform then the singular value of the watermark image is embedded to the singular value of LH sub-band of the transformed original image. In the embedding operation, multiple scaling factors are utilized on behalf of the single scaling element to get the maximum probable robustness without changing watermark lucidity. Multi-objective artificial bee colony optimization is utilized for the determination of the optimal values for multiple scaling components, which are examined against various types of attacks. For making the proposed scheme more secure, the watermark is encrypted chaotically by logistic chaotic encryption before embedding it to the host (original) image. The experimental results show excellent imperceptibility and good resiliency against a wide range of image processing attacks.</span>

RST invariant blind image watermarking schemes based on Discrete Tchebichef Transform and Singular Value Decomposition

This paper presents a new rotation, scale and translation (RST) invariant blind watermarking algorithm that combines Discrete Tchebichef Transform (DTT) with a Singular Value Decomposition (SVD) scheme. The proposed method overcomes false-positive problem, and diagonal line problem in the extracted watermark. The DTT coefficients of the image are arranged in a wavelet-like hierarchical subband scheme which generates LL (approximation), HL (vertical), LH (horizontal) and HH (diagonal) subbands. SVD is applied to all DTT subbands in order to decompose it into lower triangular, diagonal and upper triangular components. After applying SVD, the principal components of the watermark are embedded into the diagonal components of each DTT subband using appropriate scale factors. Further improve of robustness is achieved due to the combination of Arnold Transform and permutation operation which scrambles the watermark. Embedding the principal component rather than diagonal component of the watermark makes the algorithm robust to false-positive and ambiguity attacks. The visible diagonal line problem in the extracted watermark is also successively eliminated due to the embedment of principal components of watermark rather than the watermark. In addition to this, our scheme shows better robustness to most of the signal processing attacks. A suitable reverse process is applied to extract the watermark at the decoder output. The proposed method is also combined with Scale-Invariant Feature Transform (SIFT) at the output stage of the encoder. Applying SIFT in the proposed method, the geometrical attacks such as rotation, scale and translation can be restored back using the feature mapping process at the decoder input. Finally, the watermark can be recovered by applying extraction algorithm. Simulation on various kinds of standard test images demonstrated that the proposed methods show a better trade-off against imperceptibility and robustness to common attacks, geometrical attacks as well as combined attacks.

RST Invariant Blind Image Watermarking Schemes Based on Discrete Tchebichef Transform and Singular Value Decomposition

This paper presents a new rotation, scale and translation invariant blind watermarking algorithm that combines discrete Tchebichef transform (DTT) with a singular value decomposition (SVD) scheme. The proposed method overcomes false-positive problem, and diagonal line problem in the extracted watermark. The DTT coefficients of the image are arranged in a wavelet-like hierarchical sub-band scheme which generates LL (approximation), HL (vertical), LH (horizontal) and HH (diagonal) sub-bands. SVD is applied to all DTT sub-bands in order to decompose it into lower triangular, diagonal and upper triangular components. After applying SVD, the principal components of the watermark are embedded into the diagonal components of each DTT sub-band using appropriate scale factor. Further improvement of robustness is achieved due to the combination of Arnold transform and permutation operation which scrambles the watermark. Embedding the principal component rather than diagonal component of the watermark makes the algorithm robust to false-positive and ambiguity attacks. The visible diagonal line problem in the extracted watermark is also successively eliminated due to the embedment of principal components of watermark rather than the watermark. In addition to this, our scheme shows better robustness to most of the signal processing attacks. A suitable reverse process is applied to extract the watermark at the decoder output. The proposed method is also combined with scale-invariant feature transform (SIFT) at the output stage of the encoder. The geometrical attacks such as rotation, scale and translation are restored back using the feature mapping process owing to SIFT at the decoder input. Finally, the watermark can be recovered by applying extraction algorithm at the decoder output. Simulation on various kinds of standard test images demonstrated that the proposed methods shows a better trade-off against imperceptibility and robustness to common attacks, geometrical attacks as well as combined attacks.

Shift-And-Decorrelate Lifting: CAMRA for Lossless Intra Frame CFA Video Compression

In this letter, we improve lossless intra-frame compression of color filter array (CFA) video based on Camera-Aware Multi-Resolution Analysis (CAMRA). CAMRA-based compression leverages the correlation between LH and HL subbands of wavelet-transformed CFA video frames. The key contribution of this letter is an analysis showing that the chrominance components shared by LH and HL subbands of LeGall 5/3 wavelet transform are misaligned, negatively impacting the coding efficiency. To decorrelate the subbands more effectively with minimal dynamic range growth, we developed a new lifting scheme that corrects for this misalignment. We validated our theoretical analysis and the performance of the proposed compression scheme using videos of natural scenes captured in a raw format. The experimental results verify that our proposed transform improves the coding efficiency of CFA intra-frame lossless compression.

Multi-dimensional particle swarm optimization for robust blind image watermarking using intertwining logistic map and hybrid domain

Robust blind watermarking has become a vital means of copyright protection, and this paper presents a new optimal robust and blind watermarking method of grayscale images based on intertwining logistic map and a variant of particle swarm optimization (PSO) in a hybrid domain. In the proposed approach, firstly a host image is decomposed by discrete wavelet transform, and discrete cosine transform (DCT) is applied to insensitive LH and HL subbands according to human visual model. Then, optimum frequency spectra in the DCT domain are chosen to form a feature matrix for improving the robustness and transparency of watermark. Finally, a shuffled watermark image using the chaotic logistic map is inserted by modifying the largest singular values of a feature matrix pair in the singular value decomposition domain. An improved version of PSO is employed to perform multi-dimensional optimization for selection of the most qualified DCT coefficients and estimation of watermark embedding strength in terms of their significant influence on imperceptibility and robustness. The security of the proposed method is provided by intertwining logistic map. Experimental results on standard test images indicate that PSO searches efficiently optimal values of watermark embedding strength and the most suitable DCT subbands, and the proposed watermarking algorithm performs much better than the other compared schemes in imperceptibility and robustness objectives.

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.

Hybrid and blind watermarking scheme in DCuT – RDWT domain

In this paper, a hybrid and blind watermarking scheme is proposed for the protection of copyright of digital images. The scheme based on hybridization of two advance transforms such that discrete curvelet transform (DCuT) and redundant discrete wavelet transform (RDWT). The motivation behind using these two transforms combination to improve the imperceptibility of the watermarking scheme. The imperceptibility requirement of the scheme is achieved using hybrid coefficients which are achieved by applying single level RDWT to the high frequency curvelet coefficients of the cover image. The watermark information is inserted by modifying the coefficients of the wavelet coefficients of LH subband using PN sequences according to watermark bit and gain factor. The security of the proposed scheme is achieved by applying Arnold scrambling to watermark image before embedding. Experiments of the proposed scheme are conducted on various types of natural images. Experiments results show that, compared with existing schemes, the proposed scheme is robust to various attacks while having high imperceptibility. Also, the proposed scheme is performed better than many existing schemes.

Robust and Secured Medical Image Watermarking Using Daub4 and CoAST Transforms

A hybrid watermarking technique using wavelet and Shearlet transform is proposed in this paper. The DWT variant Daub4 transform model is applied on the medical image to generate different frequency sub-bands. The HL and LH sub-bands which are resistant to compression attacks are chosen for second level of transformation, a DST variant 'Cone adaptive Shearlet transform' technique is used to calculate the Shearlet coefficients of the selected sub-bands. By using SVD on the Shearlet coefficients, the singular values of watermark image are embedded into the singular values of the host image. The proposed approach is examined using three medical images and a watermark image. The experimental results show that the proposed approach is robust against JPEG compression, Geometric and Noise attacks.

Asymmetric multiple image encryption using a wavelet transform and gyrator transform

A new asymmetric multiple information security system based on a wavelet transform and gyrator transform is proposed. In the proposed method, a set of four color images are allocated to each user. Each color image is a single-level 2-D discrete wavelet transformed to decompose into LL, HL, LH, and HH sub-bands. The LL sub-bands of four images are fused to obtain a single fused image as an input image, which is segregated into R, G, and B channels. Each channel is compressed by compressive sensing with measurement matrices and modulated by a measurement-matrices-based random phase mask. In similar fashion, n sets of modulated R, G, and B channels are individually multiplexed and then gyrator transformed. The phase of each encrypted channel is embedded into the corresponding channel of the host image to obtain a watermarked channel and its amplitude is used as a common decryption key. Each set has individual decryption keys and chaotic parameters as extremely sensitive decryption keys to ensure the nonlinearity of the system. Thus, it resists potential attacks. The proposed scheme significantly reduces the data volume to be processed, transmitted, and stored, and simplifies the keys to be distributed simultaneously. The retrieved images are devoid of cross-talk noise effects. A simple optoelectronic system can be employed to realize the proposed scheme. Numerical simulation results prove the feasibility of the strategy.

Image Content Verification based on DWT and Chaotic Map Watermarking

Image content verification is to confirm the validity of the images, i.e. . To test if the image has experienced any alteration since it was made. Computerized watermarking has turned into a promising procedure for image content verification in light of its exceptional execution and capacity of altering identification. In this study, a new scheme for image verification reliant on two dimensional chaotic maps and Discrete Wavelet Transform (DWT) is introduced. Arnold transforms is first applied to Host image (H) for scrambling as a pretreatment stage, then the scrambled host image is partitioned into sub-blocks of size 2×2 in which a 2D DWT is utilized on each sub-block to produce corresponding sub-block of DWT coefficients (LL, LH, HL and HH). Meanwhile, watermark image is encrypted using the introduced chaos-based enciphering algorithm. The watermarked image is obtained by updating the approximation coefficients (LH sub-band) of each 2×2 sub-block of DWT coefficients of the host image with the enciphered watermark image bits. Different investigational tests are performed to evaluate the act of the introduced approach. Investigation results clearly present that the proposed approach can detect and localize editing attacks perfectly.

A Novel Scene-Based Video Watermarking Scheme for Copyright Protection

Abstract Many illegal copies of original digital videos are being made, as they can be replicated perfectly through the Internet. Thus, it is extremely necessary to protect the copyrights of the owner and prevent illegal copying. This paper presents a novel approach to digital video watermarking for copyright protection using two different algorithms, whereby successive estimation of a statistical measure was used to detect scene boundaries and watermark was embedded in the detected scenes with discrete wavelet transform. Haar wavelet was used for decomposition. For embedding, the approaches used were (i) the detailed subband (LH subband) and (ii) the approximate subband (LL subband) of the cover video. Imperceptibility, robustness, and channel capacity were measured using both algorithms. The system was tested for robustness in the presence of 15 different attacks of five different categories, and, under multiple attacks, ensured that a wide spectrum of attack analysis has been done. The performance metrics measured included mean square error, peak signal-to-noise ratio, structural similarity index, normalized correlation, and bit error rate. The experimental results demonstrated the better visual imperceptibility and improved performance in terms of normalized correlation and bit error rate with embedding using the LL subband. Comparative analysis with existing schemes proved the improved robustness, better imperceptibility, and reduced computational time of both the proposed schemes.

A robust blind hybrid image watermarking scheme in RDWT-DCT domain using Arnold scrambling

To compromise between imperceptibility and robustness property of robust image watermarking technique, a RDWT-DCT based blind image watermarking scheme using Arnold scrambling is presented in this paper. Firstly, RDWT (Redundant Discrete Wavelet Transform) is applied to each gray scale cover image block after the image is decomposed into fixed size non overlapping blocks. Secondly, the binary watermark logo is encrypted by Arnold chaotic map and reshaped to a sequence to improve the security of the logo. In the subsequent step, DCT (Discrete Cosine Transform) is employed on each LH subband of the non-overlapping host image block. Finally, after zigzag scanning of each DCT block a binary bit of watermark is embedded into each block by adjusting some middle significant AC coefficients using repetition code. Experimental results show that robustness is achieved by recovering satisfactory watermark data from the reconstructed cover image after applying common geometric transformation attacks (like rotation, cropping, scaling, shearing and deletion of lines or column operation etc.), common enhancement technique attacks (like lowpass filtering, histogram equalization, sharpening, gamma correction, noise addition etc.) and JPEG compression attacks. The proposed scheme is also tested to verify the robustness performance against standard benchmark software "Checkmark" and satisfactory results are achieved against the Checkmark attacks such as Hard and Soft Thresholding, Template Removal, Warping, Dithering, Remodulation and Downsampling/Upsampling etc.

Wavelet transform based technique for text image localization

In this paper, a robust technique based on discrete wavelet transform, edge detection, and morphology operation for scene text detection is proposed. There are several stages in the proposed method. In the first stage, a single wavelet decomposition LH, HL and HH subbands are applied for detecting edges in original scene text image. The projection technique is applied in the second stage to preliminary detect text and non-text pixels. In third stage, 4-connected components are applied, and then area geometric feature is used as threshold to remove non-text region. At last stage, morphological operations are applied to connect isolated text components and to remove non-text regions. The proposed method is applied on a various images such as images of low contrast, complex background images and images of different fonts and size of text. The experimental results show that the proposed method can detect regions of the text perfectly.

A novel moving object segmentation framework utilizing camera motion recognition for H.264 compressed videos

This paper presents a novel coarse to fine moving object segmentation framework for H.264/AVC compressed videos. The proposed framework integrates the global motion estimation and global motion compensation steps in the segmentation pipeline unlike previous techniques which did not consider such an integration. The integration is based on testing for presence of global motion by classifying the interframe motion vectors into moving camera class and still camera class. The decision boundary separating these two classes is learnt from the training video data. The integration automates the moving object segmentation to be applicable for static, moving and combination of static/moving camera cases which to the best of our knowledge has not been carried out earlier. Further, a novel coarse segmentation technique is proposed by decomposing the inter-frame motion vectors into wavelet sub-bands and utilizing logical operations on LH, HL and HH sub-band wavelet coefficients. The premise is based on the fact that since the LH, HL and HH sub-bands contain the detail information pertaining to horizontal, vertical and diagonal moving blocks respectively, they can be exploited to identify the coarse moving boundaries. The coarse segmentation is fast in comparison to state-of-the-art coarse segmentation methods as demonstrated by our experiments. Finally, these coarse boundaries are modeled in an energy minimization framework and shown that by minimizing the energy using graph cut optimization the segmentation is refined to obtain the fine segmentation. The proposed framework is tested on a number of standard video sequences encoded with H.264/AVC JM encoder and comparison is carried out with state-of-the-art compressed domain moving object segmentation methods as well as with an existing state-of-the-art pixel domain method to establish and validate the proposed moving object segmentation framework.