Nowadays, medical imaging equipments produce digital form of medical images. In a modern health care environment, new systems such as PACS (picture archiving and communication systems), use the digital form of medical image too. The digital form of medical images has lots of advantages over its analog form such as ease in storage and transmission. Medical images in digital form must be stored in a secured environment to preserve patient privacy. It is also important to detect modifications on the image. These objectives are obtained by watermarking in medical image. In this paper, we present a dual and oblivious (blind) watermarking scheme in the contourlet domain. Because of importance of ROI (region of interest) in interpretation by medical doctors rather than RONI (region of non-interest), we propose an adaptive dual watermarking scheme with different embedding strength in ROI and RONI. We embed watermark bits in singular value vectors of the embedded blocks within lowpass subband in contourlet domain. The values of PSNR (peak signal-to-noise ratio) and SSIM (structural similarity measure) index of ROI for proposed DICOM (digital imaging and communications in medicine) images in this paper are respectively larger than 64 and 0.997. These values confirm that our algorithm has good transparency. Because of different embedding strength, BER (bit error rate) values of signature watermark are less than BER values of caption watermark. Our results show that watermarked images in contourlet domain have greater robustness against attacks than wavelet domain. In addition, the qualitative analysis of our method shows it has good invisibility. The proposed contourlet-based watermarking algorithm in this paper uses an automatically selection for ROI and embeds the watermark in the singular values of contourlet subbands that makes the algorithm more efficient, and robust against noise attacks than other transform domains. The embedded watermark bits can be extracted without the original image, the proposed method has high PSNR and SSIM, and the watermarked image has high transparency and can still conform to the DICOM format.

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A dual adaptive watermarking scheme in contourlet domain for DICOM images.

Healthcare institutions adapt cloud based archiving of medical images and patient records to share them efficiently. Controlled access to these records and authentication of images must be enforced to mitigate fraudulent activities and medical errors. This paper presents a zero-watermarking scheme implemented in the composite Contourlet Transform (CT)—Singular Value Decomposition (SVD) domain for unambiguous authentication of medical images. Further, a framework is proposed for accessing patient records based on the watermarking scheme. The patient identification details and a link to patient data encoded into a Quick Response (QR) code serves as the watermark. In the proposed scheme, the medical image is not subjected to degradations due to watermarking. Patient authentication and authorized access to patient data are realized on combining a Secret Share with the Master Share constructed from invariant features of the medical image. The Hu's invariant image moments are exploited in creating the Master Share. The proposed system is evaluated with Checkmark software and is found to be robust to both geometric and non geometric attacks.

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A QR Code Based Zero-Watermarking Scheme for Authentication of Medical Images in Teleradiology Cloud

Image watermarking in wavelet domain has been found useful for copyright protection and rightful ownership. Classical wavelet transforms, like discrete wavelet transform (DWT), are shift sensitive and provide information in horizontal, vertical and diagonal directions only. Shift invariance and directional information are required for better reconstruction of images. In this work, we propose a semi-blind gray scale image watermarking technique in redundant wavelet domain. The primary focus of this research is to highlight the usefulness of redundant wavelet transforms in image watermarking. We have used nonsubsampled contourlet transform (NSCT) and redundant discrete wavelet transform (RDWT). These redundant transforms are shift invariant. Also, NSCT provides rich directional information. Thus, they overcome the shortcomings of DWT and are more useful in image watermarking. We have integrated singular value decomposition (SVD) in the proposed method. We use NSCT-RDWT-SVD decomposition for single and dual image watermarking. For single watermark embedding, cover images are sub-sampled followed by one level NSCT and RDWT decomposition. SVD has been applied on obtained RDWT coefficients. In the same way, image watermark has been processed and NSCT-RDWT-SVD decomposition has been applied on it. SVD coefficients of the cover image and watermark image have been combined using scaling factor. Inverse SVD-RDWT-NSCT operation together with reverse sub-sampling provides watermarked image. For extraction of the watermark, we follow the NSCT-RDWT-SVD decomposition and SVD coefficients have been separated by the same scaling factor that was used in embedding. In the dual watermarking, Arnold transform has been used for encryption of the text watermark and rest of the steps are similar to single watermarking. NSCT, RDWT and SVD improve the performance of the proposed method against geometrical and image processing attacks for single and dual image watermarking. Experiments have been carried over standard images and results have been shown for natural and medical images. Qualitative and quantitative evaluations in terms of peak signal to noise ratio (PSNR), correlation coefficient (CC), bit error rate (BER) and structural similarity index metric (SSIM) show that the proposed method is suitable for single and dual image watermarking, and outperforms existing methods.

Hybrid semi-blind image watermarking in redundant wavelet domain

In this paper, a novel blind color image watermarking based on Contourlet transform and Hessenberg decomposition is proposed to protect digital copyright of color image. Firstly, each color channel of the host image is transformed by Contourlet transform and its low frequency sub-band is divided into 4ź×ź4 non-overlap coefficient block. Secondly, the coefficient block selected by MD5-based Hash pseudo-random algorithm is decomposed by Hessenberg decomposition. Thirdly, the watermark information permuted by Arnold transform is embedded into the biggest energy element of the upper Hessenberg matrix by quantization technique. In extraction process, the quantization strength is used for blindly extracting watermark information from the attacked host image without the help of any original image. The results show that the proposed scheme has higher imperceptibility and robustness against most common image attacks in comparison with other related methods.

A novel blind color image watermarking based on Contourlet transform and Hessenberg decomposition

Medical images are of high importance and patient data must be kept confidential. In this chapter, we discuss a new hybrid transform domain technique for medical image watermarking and provide a detailed analysis of existing image watermarking methods. The proposed method uses a combination of nonsubsampled contourlet transform (NSCT), discrete cosine transform (DCT) and singular value decomposition (SVD) to achieve high capacity, robustness and imperceptibility. This method is non blind which requires cover image in receiver to extract watermarked image. Cover and watermark images are pre-processed in order to ensure accurate extraction of watermark. In this approach, we have considered medical images as cover and electronic patient record (EPR) is used as secret message. EPR message is embedded into selected sub band of cover image with selected gain factor so that there should be a good trade off among imperceptibility, robustness and capacity. NSCT increases hiding capacity and is more resistant to geometrical attacks. The combination of NSCT with DCT and SVD enhanced the perceptual quality and security of watermarked image. Experimental demonstration proved that the proposed method provides high robustness against geometrical and signal processing attacks in terms of peak signal to noise ratio (PSNR) and correlation coefficient (CC).

SVD-DCT Based Medical Image Watermarking in NSCT Domain

In this paper, we propose a new robust hybrid watermarking technique based on recently introduced contourlet transform and singular value decomposition. After applying the contourlet transform for the original image, we select the low frequency directional sub band coefficients and apply singular value decomposition. The singular values of the original image are then modified by the singular values of contourlet transformed binary logo watermark image. Combination of these two transforms on image improves the performance of watermarking algorithm. It has been observed that, in comparison with other contourlet based and wavelet based methods, the proposed method shows the higher imperceptibility and robustness against common image processing attacks such as Jpeg compression, Jpeg 2000 compression, resizing, median filtering, histogram equalization, sharpening, and Gama correction.

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A hybrid watermarking scheme using contourlet transform and singular value decomposition

The paper proposes a novel robust watermarking technique based on newly introduced Nonsubsampled contourlet transform(NSCT) and singular value decomposition(SVD) for multimedia copyright protection. The NSCT can give the asymptotic optimal representation of the edges and contours in image by virtue of the characteristics of good multi resolution shift invariance and multi directionality. After decomposing the host image into sub bands, we choose the low frequency directional sub band and apply singular value decomposition. The singular values of the original image are then modified by the singular values of nonsubsampled contourlet transformed visual grayscale logo watermark image. This hybrid approach improves the performance of the watermarking technique compared to earlier techniques. Experimental results shows that the hybrid technique is resilient to various linear and non linear filtering ,JPEG compression, JPEG2000 compression, Histogram equalization, Grayscale inversion, Contrast adjustment, gamma correction, alpha mean ,cropping ,Gaussian noise, scaling etc.

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A Robust Watermarking Technique based on Nonsubsampled Contourlet Transform and SVD

This paper presents a low complexity two dimensional (2D) circular symmetric Finite Impulse Response (FIR) filter design and implementation of architecture. The optimized circular symmetric 2D FIR filter is designed using a modified Park–McClellan transformation method and filter coefficients are quantized using a canonical signed digit (CSD) binary number format. The CSD encoded coefficients are optimized to reduce the number of adder/subtractors using common subexpression elimination (CSE) algorithms. Based on the modified filter coefficients, the two structures fully direct form and hybrid-II form 2D FIR filter architectures are implemented using CSD and CSD with Horizontal CSE and Vertical CSE techniques. The proposed architectures compared with the conventional symmetry 2D filters and state-of-the-art architectures in terms of area, power, and speed.

Design and implementation of low complexity circularly symmetric 2D FIR filter architectures

The authors propose a new hybrid watermarking scheme for copyright protection of color images using contourlet transform and singular value decomposition. The host color image and color watermark images are decomposed into directional sub- bands using contourlet transform and then applied Singular value decomposition to mid frequency subband coefficients. The singular values of mid frequency subband coefficients of color watermark image are embedded into singular values of mid frequency sub-band coefficients of host color image in Red, Green and Blue color spaces simultaneously based on spread spectrum technique. The experimental results shows that the proposed hybrid watermarking scheme is robust against common image processing operations such as, JPEG, JPEG 2000 compression, cropping, Rotation, histogram equalization, low pass filtering ,median filtering, sharpening, shearing ,salt & Pepper noise, Gaussian noise, grayscale conversion etc. It has also been shown the variation of visual quality of watermarked image for different scaling factors. The comparative analysis reveals that the proposed watermarking scheme out performs the color image watermarking schemes reported recently.

https://www.ijcaonline.org/volume20/number8/pxc3873314.pdf

A New SVD based Hybrid Color Image Watermarking for Copyright Protection using Contourlet Transform

This paper presents an analysis to image denoising using discrete wavelet transformation(DWT) and complex wavelet transformation(CWT). The affect of image denoising on the variation of image noise variance and the selection of threshold value is analyzed. The image denoising effect based on soft thresholding and hard thresholding is carried out and evaluated for different noise variances, and different threshold values. The quality evaluation of denoising operation is carried out using PSNR observation, and found to be higher for complex wavelet transformation than the DWT approach. The soft thresholding result in higher PSNR for higher noise variance and for the higher threshold values. The denoising performance for CWT is observed to be improved with increase in threshold value under a constant noise effect. In the variation of noise effect for a constant threshold the PSNR decreases, however the CWT is observed to have higher denoising efficiency compared to conventional DWT approach.

C. Venkata Narasimhulu

Papers

A hybrid watermarking scheme using contourlet transform and singular value decomposition

A Robust Watermarking Technique based on Nonsubsampled Contourlet Transform and SVD

Design and implementation of low complexity circularly symmetric 2D FIR filter architectures

A New SVD based Hybrid Color Image Watermarking for Copyright Protection using Contourlet Transform

Transformations analysis for image denoising using complex wavelet transform