Rotation Invariance in 2D-FRFT with Application to Digital Image Watermarking

In this proposed work, a dual image watermarking algorithm is used to protect the data against copyright violations. In this work, the DICOM image is used as a host image. Two watermark images used are the MNNIT logo and the personal data of the patient. This method utilizes the advantages of Schur decomposition, lifting wavelet transform (LWT), discrete cosine transform (DCT) and singular value decomposition (SVD). The scaling factor is a vital parameter of watermarking technique. The firefly optimization technique is used to get the optimized scaling factor. The Speeded-up robust features (SURF) are used for watermarking authentication. To evaluate the performance of the proposed algorithm, peak signal-to-noise ratio (PSNR), normalized correlation coefficient (NCC), and structural similarity index measurement (SSIM) are used. The proposed method is tested against various attacks such as Salt and Pepper noise, Gaussian noise, Gaussian low pass filter, Average filter, Median filter, Histogram equalization, Sharpening, Rotation and Region of interest filtering. The proposed algorithm shows a high level of robustness and imperceptibility. It is found that the features of the input host image and the watermarked image are matching correctly on applying the SURF technique.

Digital images, particularly medical images, are prone to various noise attacks, such as additive, multiplicative, etc. Salt and pepper noise (SPN) is a type of multiplicative noise that degrades image quality and complicates identification, potentially leading to inaccurate diagnoses. Removing SPN is crucial yet challenging as noise removal can also eliminate important edge details. This study addresses the challenge of removing SPN without losing edge details. Existing SPN filtering algorithms, such as Average Filter (AF), Median Filter (MF), Switched MF (SMF), Adaptive MF (AMF), and Decision-based MF (DMF), perform poorly under high SPN attacks. We propose two effective SPN filters, CA_SPN1 and CA_SPN2, under the framework of Cellular Automata (CA) and MF. CA_SPN1 excels at high SPN levels, while CA_SPN2, a combination of CA_SPN1 and AMF, is effective across all SPN levels. Quality evaluations using Image Quality Assessment (IQA) metrics – Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM), Figure of Merit (FOM), and Perceptual Similarity (PSIM) – demonstrate that the proposed algorithms restore images more effectively while preserving edge details compared to state-of-the-art algorithms. Furthermore, experimental results confirm the superior restoration quality of the proposed filters, particularly under high SPN conditions.

This paper presents a new robust and invisible blind watermarking approach of colour images for copyright protection in hybrid DWT-DCT-SVD domain. In the proposed method, firstly the luminance component (Y) of the cover image is decomposed up to one level of discrete wavelet transform (DWT) coefficients and the low frequency band (LL) is transformed by discrete cosine transform (DCT). Then several selected low and intermediate frequency DCT coefficients of each block are extracted to generate a feature matrix and singular value decomposition (SVD) transform is applied to the feature matrix. Finally the watermark information is embedded by modifying the singular values of the feature matrix. Experimental results demonstrate that the proposed approach outperforms some popular existing watermarking methods in robustness against median filtering, Gaussian filtering, salt and pepper noise, average filtering, Gaussian noise, histogram equalisation, and so on, especially in case of lossy JPEG compression in addition to good imperceptibility.

In this research, we introduce an efficient blind watermarking method for gray image based on wavelet tree quantization using adaptive threshold in extraction process. Based on difference value between two largest coefficients, each scrambled binary watermark bit is embedded into each block which created by four LH3 coefficients and one LH4 coefficient. In extraction process, we compare difference value in each block to adaptive threshold to recover watermark bit. The quality of extracted watermark depends on the threshold which is determined by the Weighted Within-Class Variance algorithm. Performance of proposed method is represented through experimental results under various attacks such as, Histogram Equalization, Cropping, Low-pass Filtering, Gaussian noise, Salt & Pepper noise and JPEG compression. 

In the paper, a robust blind watermarking method is introduced for gray-scale images based on wavelet tree quantization with an adaptive threshold in the extraction. Every block of 2×2 coefficients of High-Low subbands of the Wavelet tranform are grouped in a block through the parent-child relationship of the wavelet tree. Every scrambled binary watermark bit is embedded into each block based on the difference value of two largest coefficients. The watermark is recovered by comparing the difference values in each block to an adaptive threshold. The accuracy of an extracted watermark depends on the threshold which is determined by minimizing the sum of weighted within-class variance. The performance of the proposed watermarking method is represented through experimental results under various types of attack such as, Histogram Equalization, Cropping, Low-pass Filtering, Gaussian noise, Salt & Pepper noise and JPEG compression. In additions, the proposed method is also compared to recent methods in the extraction performance.

Cellular automata based color image watermarking using non sub sampled contourlet transform (NSCT) and singular value decomposition (SVD) is presented in this paper. Game of life (GOL) cellular automata is used to scramble binary watermark so that no one can recover the watermark without secret scrambling keys. Because of the salient features like multiscale, multidirection and shift invariance of NSCT, 2-level NSCT is applied to red, green and blue component of RGB cover image. Most of the perceptual content of an image focuses on low frequency subband of NSCT and the singular values taken from low frequency subband have certain stability. So a modest change in the singular values taken from low frequency subband of NSCT is applicable. In this proposed scheme, each singular value of scrambled binary watermark is embedded in fixed location of singular value matrix of low frequency subbands of NSCT of red, green and blue components. The scheme offers security, imperceptibility and robustness against various image processing and geometric attacks like Gaussian white noise, salt and pepper noise, median filtering, JPEG compression, cropping and rotation. The proposed scheme is compared with existing watermarking schemes in terms of Peak Signal to Noise ratio (PSNR), Normalized Correlation (NC)and provides satisfactory performance than other schemes.

In recent years, with the development of the information society, digital images can be easily uploaded and downloaded. Against this background, instances of plagiarism and tampering with images have been increasing. Therefore, it is necessary to develop robust watermarking for the copyright protection of digital images. In this study, we propose a blind digital image watermarking method based on dual-tree complex discrete wavelet transform and quantization. We apply this wavelet transform to the original image and embed two watermarked images of different sizes using quantization index modulation and relative modulation. Quantization index modulation is robust against geometric attacks. Relative modulation is robust against noise addition. The results of our experiments show that our method is robust against Gaussian noise, salt and pepper noise, cropping, and Jpeg compression. The experimental results show that the watermark can be extracted by Gaussian noise, salt and pepper noise, cropping, Jpeg compression. In addition, we visually check the extracted watermarked images. Furthermore, we compare three methods: one using dual-tree complex discrete wavelet transform and sliding window. The second method is based on discrete wavelet transform, discrete cosine transform, and singular value decomposition. The third method is based on Discrete Cosine Transform and RM, QIM. By comparing these three methods with the existing methods, we confirmed the significance and performance of our method.

Blind optimum detector for robust image watermarking in nonsubsampled shearlet Domain

This paper presents a robust blind frequency domain watermarking scheme based on chaotic maps. The proposed scheme embeds a black and white watermark logo in the midband components of a host image according to a discrete wavelet transform. Each watermark bit is embedded into a small submatrix of selected second level subbands of an image resulting from iterated applications of a two-dimensional discrete wavelet transform. This scheme embeds two copies of the watermark using two different methods, in two different subbands of the image. At the cost of embedding capacity, this results in improving the security and robustness of the watermarking scheme. Experimental results demonstrate that the suggested scheme provides imperceptibility and robustness against image processing attacks such as JPEG compression, low-pass filtering, median filtering, Gaussian noise, scaling, rotating, cropping, histogram equalization, and gamma correction. Experimental results also show superior robustness of the suggested scheme over existing algorithms with a similar approach. Copyright © 2013 John Wiley & Sons, Ltd.

We present a technique for irreversible watermarking approach robust to affine transform attacks in camera, biomedical and satellite images stored in the form of monochrome bitmap images. The watermarking approach is based on image normalisation in which both watermark embedding and extraction are carried out with respect to an image normalised to meet a set of predefined moment criteria. The normalisation procedure is invariant to affine transform attacks. The result of watermarking scheme is suitable for public watermarking applications, where the original image is not available for watermark extraction. Here, direct-sequence code division multiple access approach is used to embed multibit text information in DCT and DWT transform domains. The proposed watermarking schemes are robust against various types of attacks such as Gaussian noise, shearing, scaling, rotation, flipping, affine transform, signal processing and JPEG compression. Performance analysis results are measured using image processing metrics.

In this paper, we present four denoising algorithms dedicated to the division of focal plane (DoFP) polarization image sensors, including the average filtering, median filtering, Wiener filtering and wavelet threshold denoising algorithms. Compared with the previous implementations solely based on the Gaussian noise model, this paper, for the first time, covers the non-Gaussian noises, such as the salt & pepper noise and Poisson noise. According to our extensive experimental results, the wavelet threshold denoising outperforms for suppressing the Gaussian noise; while the median filtering and the Wiener filtering outperform for suppressing the low-density salt & pepper noise and Poisson noise, respectively.

In this paper, a blind image watermarking scheme based on discrete wavelet transform (DWT) and singular value decomposition (SVD) is proposed. In this scheme, DWT is applied on ROI (region of interest) of the medical image to get different frequency subbands of its wavelet decomposition. On the low frequency subband LL of the ROI, block-SVD is applied to get different singular matrices. A pair of elements with similar values is identified from the left singular value matrix of these selected blocks. The values of these pairs are modified using certain threshold to embed a bit of watermark content. Appropriate threshold is chosen to achieve the imperceptibility and robustness of medical image and watermark contents respectively. For authentication and identification of original medical image, one watermark image (logo) and other text watermark have been used. The watermark image provides authentication whereas the text data represents electronic patient record (EPR) for identification. At receiving end, blind recovery of both watermark contents is performed by a similar comparison scheme used during the embedding process. The proposed algorithm is applied on various groups of medical images like X-ray, CT scan and mammography. This scheme offers better visibility of watermarked image and recovery of watermark content due to DWT-SVD combination. Moreover, use of Hamming error correcting code (ECC) on EPR text bits reduces the BER and thus provides better recovery of EPR. The performance of proposed algorithm with EPR data coding by Hamming code is compared with the BCH error correcting code and it is found that later one perform better. A result analysis shows that imperceptibility of watermarked image is better as PSNR is above 43 dB and WPSNR is above 52 dB for all set of images. In addition, robustness of the scheme is better than existing scheme for similar set of medical images in terms of normalized correlation coefficient (NCC) and bit-error-rate (BER). An analysis is also carried out to verify the performance of the proposed scheme for different size of watermark contents (image and EPR data). It is observed from analysis that the proposed scheme is also appropriate for watermarking of color image. Using proposed scheme, watermark contents are extracted successfully under various noise attacks like JPEG compression, filtering, Gaussian noise, Salt and pepper noise, cropping, filtering and rotation. Performance comparison of proposed scheme with existing schemes shows proposed scheme has better robustness against different types of attacks. Moreover, the proposed scheme is also robust under set of benchmark attacks known as checkmark attacks.

The popular histogram equalisation (HE) technique, which was developed to improve the image contrast, sometimes may also be misused to hide intensity variations in tampered images with ill intention. The authors investigate how existing image forensic techniques may fail to detect HE operation in highly compressed and low-resolution images. They then propose an algorithm to detect whether a given image (either uncompressed or JPEG compressed) has undergone the HE process or not. It is based on the frequency domain analysis of image histogram and exploits the difference in DC and AC coefficients in histogram's discrete Fourier transform. It can detect HE operation even if the image is saved in JPEG format after the equalisation, where most the existing algorithms fail. The extensive computer simulations over large dataset show the effectiveness of the proposed algorithm.

In this paper, we focus on the robustness in noise tolerance of spatial domain optical flow and we present a performance study of bidirectional confidential with median filter on spatial domain optical flow (spatial correlation, local based, and global based) under non Gaussian noise where several noise tolerance models on spatial domain optical flow are used in comparison. The experiment results are investigated on robustness under noisy condition by using non Gaussian noise (Poisson Noise, Salt & Pepper noise, and Speckle Noise) in contamination with several standard sequences. The experiment concentrates on Error Vector Magnitude (EVM) as a performance indicator where the result in motion vector (MV) of each method is used to compare with the ground truth vector in the experimental performance analysis.

Laser image often mixes with salt and pepper noise when obtained and transmitted by image sensor. The salt and pepper noise not only makes the quality of laser image deteriorated but also causes the detail feature of laser image flooded which contains very important structure information. To remove salt and pepper noise effectively meanwhile ensure image details clear and completed, a Novel Adaptive Switching Median (NASM) filter based on local salt and pepper noise density is presented in this paper. Pixel points are divided into salt and pepper noise points and signal points according to two level detection mechanisms firstly, then, local salt and pepper noise density is introduced here to determined filter window of every noise point, only noise points are filtered by different size window adaptively whereas signal points are kept unprocessed finally. Through analyzing of experimental results, it shows that NASM filter can remove salt and pepper noise effectively meanwhile protect image details well thus getting better filtering performance compared with Traditional Median (TM) filter and other improved Switching Median (SM) filters for laser image.