Hae-Yeoun Lee

Reversible data hiding exploiting spatial correlation between sub-sampled images

Reversible data hiding enables host media to be restored from marked media without any loss of host information. Since this reversibility helps to make right decision during image analysis, it is highly desired in quality-sensitive imagery where even the minimal distortion introduced by embedding data is unacceptable. In this paper, we propose a reversible data hiding method that modifies the difference histogram between sub-sampled images. It exploits the high spatial correlation inherent in neighboring pixels to achieve high capacity and imperceptible embedding. On various test images including 16-bit images, we demonstrate the validity of our proposed method by comparing to other existing reversible data hiding algorithms. Experimental results support that our method provides high embedding capacity while keeping the distortions at a low level.

Robust image watermarking using local invariant features

This paper addresses a novel robust watermarking method for digital images using local invariant features. Most previous water- marking algorithms are unable to resist geometric distortions that desyn- chronize the location where copyright information is inserted. We pro- pose a watermarking method that is robust to geometric distortions. In order to resist geometric distortions, we use a local invariant feature of the image called the scale-invariant feature transform SIFT, which is invariant to translation and scaling distortions. The watermark is inserted into the circular patches generated by the SIFT. Rotation invariance is achieved using the translation property of the polar-mapped circular patches. Our method belongs to the blind watermark, because we do not need the original image during detection. We have performed an inten- sive simulation to show the robustness of the proposed method. The simulation results support the contention that our method is robust against geometric distortion attacks as well as signal-processing attacks. We have compared our results with those of other methods, and our method outperforms them.

Contrast-enhanced peripheral MR angiography from the abdominal aorta to the pedal arteries: combined dynamic two-dimensional and bolus-chase three-dimensional acquisitions.

Wang Y, Winchester PA, Khilnani NM, et al. Contrast-enhanced peripheral MR angiography from the abdominal aorta to the pedal arteries: Combined dynamic two-dimensional and bolus-chase three-dimensional acquisitions. Invest Radiol 2001;36:170–177. rationale and objectives. To obtain reliable contrast-enhanced peripheral MR angiography for imaging peripheral vascular disease from the abdominal aorta to the pedal arteries. methods.A protocol consisting of contrast-enhanced, dynamic two-dimensional (2D) acquisition at the feet and calf and bolus-chase three-dimensional (3D) acquisition from the abdominal aorta to the calf was developed and applied in patients with peripheral vascular disease. The performance of this integrated protocol was assessed in 89 consecutive patients. results.The bolus-chase 3D acquisition was of diagnostic quality in 100% of the acquisitions in the abdomen, 96% in the thigh, and 43% in the calf. The poor quality of the calf acquisitions was due to insufficient spatial resolution, poor arterial signal, and venous contamination. Diagnostic-quality images were obtained in 100% of the dynamic 2D acquisitions of the calf and 98% of the feet. conclusions.The combined dynamic 2D and bolus-chase 3D contrast-enhanced MR angiography technique provides diagnostic images of the entire lower extremity.

Automatic Left Ventricle Segmentation Using Iterative Thresholding and an Active Contour Model With Adaptation on Short-Axis Cardiac MRI

An automatic left ventricle (LV) segmentation algorithm is presented for quantification of cardiac output and myocardial mass in clinical practice. The LV endocardium is first segmented using region growth with iterative thresholding by detecting the effusion into the surrounding myocardium and tissues. Then the epicardium is extracted using the active contour model guided by the endocardial border and the myocardial signal information estimated by iterative thresholding. This iterative thresholding and active contour model with adaptation (ITHACA) algorithm was compared to manual tracing used in clinical practice and the commercial MASS Analysis software (General Electric) in 38 patients, with Institutional Review Board (IRB) approval. The ITHACA algorithm provided substantial improvement over the MASS software in defining myocardial borders. The ITHACA algorithm agreed well with manual tracing with a mean difference of blood volume and myocardial mass being 2.9 ± 6.2 mL (mean ± standard deviation) and -0.9 ± 16.5 g, respectively. The difference was smaller than the difference between manual tracing and the MASS software (approximately -20.0 ± 6.9 mL and -1.0 ± 20.2 g, respectively). These experimental results support that the proposed ITHACA segmentation is accurate and useful for clinical practice.

Extraction of digital elevation models from satellite stereo images through stereo matching based on epipolarity and scene geometry

Abstract This paper addresses the problem of generating digital elevation models from satellite images taken by linear pushbroom cameras. Since there exist unique geometric properties for linear pushbroom images, we argue that the conventional DEM generation schemes developed for perspective images are not suitable for satellite images. Using the geometric properties of linear pushbroom images, we design a new matching strategy optimized for linear pushbroom image in three aspects: conjugate search method, correlation patch design and match sequence determination. We will discuss in what aspect conventional approaches and our new approach differ and show how performance has improved by hiring proper techniques. A series of experiments using SPOT panchromatic stereo pairs showed that our approach outperformed conventional approaches in terms of accuracy and processing time.

Improved steganographic method preserving pixel-value differencing histogram with modulus function

We herein advance a secure steganographic algorithm that uses a turnover policy and a novel adjusting process. Although the method of Wang et al. uses Pixel-Value Differencing (PVD) and their modulus function provides high capacity and good image quality, the embedding process causes a number of artifacts, such as abnormal increases and fluctuations in the PVD histogram, which may reveal the existence of the hidden message. In order to enhance the security of the algorithm, a turnover policy is used that prevents abnormal increases in the histogram values and a novel adjusting process is devised to remove the fluctuations at the border of the subrange in the PVD histogram. The proposed method therefore eliminates all the weaknesses of the PVD steganographic methods thus far proposed and guarantees secure communication. In the experiments described herein, the proposed algorithm is compared with other PVD steganographic algorithms by using well-known steganalysis techniques, such as RS-analysis, steganalysis for LSB matching, and histogram-based attacks. The results support our contention that the proposed method enhances security by keeping the PVD histogram similar to the cover, while also providing high embedding capacity and good imperceptibility to the naked eye.

Evaluation of feature extraction techniques for robust watermarking

This paper addresses feature extraction techniques for robust watermarking. Geometric distortion attacks desynchronize the location of the inserted watermark and hence prevent watermark detection. Watermark synchronization, which is a process of finding the location for watermark insertion and detection, is crucial to design robust watermarking. One solution is to use image features. This paper reviews feature extraction techniques that have been used in featurebased watermarking: the Harris corner detector and the Mexican Hat wavelet scale interaction method. We also evaluate the scale-invariant keypoint extractor in comparison with other techniques in aspect of watermarking. After feature extraction, the set of triangles is generated by Delaunay tessellation. These triangles are the location for watermark insertion and detection. Redetection ratio of triangles is evaluated against geometric distortion attacks as well as signal processing attacks. Experimental results show that the scale-invariant keypoint extractor is appropriate for robust watermarking.

Real-time video watermarking system on the compressed domain for high-definition video contents: Practical issues

Everyday, we encounter high-quality multimedia contents from HDTV broadcasting, DVD, and high-speed Internet services. These contents are, unhappily, processed and distributed without protection. This paper proposes a practical video watermarking technique on the compressed domain that is real-time and robust against video processing attacks. In particular, we focus on video processing that is commonly used in practice such as downscaling resolution, framerate changing, and transcoding. Most previous watermarking algorithms are unable to survive when these processings are strong or composite. We extract low frequency coefficients of frames in fast by partly decoding videos and apply a quantization index modulation scheme to embed and detect the watermark. On an Intel architecture computer, we implement a prototype system and measure performance against video processing attacks frequently occur in the real world. Simulation results show that our video watermarking system satisfies real-time requirements and is robust to protect the copyright of HD video contents.

Practical, Real-Time, and Robust Watermarking on the Spatial Domain for High-Definition Video Contents

Commercial markets employ digital right management (DRM) systems to protect valuable high-definition (HD) quality videos. DRM system uses watermarking to provide copyright protection and ownership authentication of multimedia contents. We propose a real-time video watermarking scheme for HD video in the uncompressed domain. Especially, our approach is in aspect of practical perspectives to satisfy perceptual quality, real-time processing, and robustness requirements. We simplify and optimize human visual system mask for real-time performance and also apply dithering technique for invisibility. Extensive experiments are performed to prove that the proposed scheme satisfies the invisibility, real-time processing, and robustness requirements against video processing attacks. We concentrate upon video processing attacks that commonly occur in HD quality videos to display on portable devices. These attacks include not only scaling and low bit-rate encoding, but also malicious attacks such as format conversion and frame rate change.

Geometrically invariant watermarking: synchronization through circular Hough transform

This paper addresses a geometrically invariant watermarking method for digital images. Most previous watermarking algorithms perform weakly against geometric distortions, which desynchronize the location for the inserted watermark. Watermark synchronization, which is a process for finding the location for watermark insertion and detection, is crucial for robust watermarking. In this paper, we propose a watermarking method that is robust to geometric distortions. In order to synchronize the location for watermark insertion and detection, we use circular Hough transform, which extracts circular features that are invariant to geometric distortions. The circular features are then watermarked using additive way on the spatial domain. Our method belongs to the category of blind watermarking techniques, because we do not need the original image during detection. Experimental results support the contention that our method is useful and considerably robust against both geometric distortion attacks and signal processing attacks as listed in Stirmark 3.1.