The growth of new imaging technologies has created a need for techniques that can be used for copyright protection of digital images. Copyright protection involves the authentication of image content and/or ownership and can be used to identify illegal copies of a (possibly forged) image. One approach for copyright protection is to introduce an invisible signal known as a digital watermark in the image. In this paper, we describe digital image watermarking techniques, known as perceptually based watermarks, that are designed to exploit aspects of the human visual system. In the most general sense, any watermarking technique that attempts to incorporate an invisible mark into an image is perceptually based. However, in order to provide transparency (invisibility of the watermark) and robustness to attack, more sophisticated use of perceptual information in the watermarking process is required. Several techniques have been introduced that incorporate a simple visual model in the marking procedure. Such techniques usually take advantage of frequency selectivity and weighing to provide some perceptual criteria in the watermarking process. Even more elaborate visual models are used to develop schemes that not only take advantage of frequency

Lossy compression algorithms used in digital video systems produce artifacts whose visibility strongly depends on the actual image content. Simple error measures such as RMSE or PSNR, albeit popular, ignore this important fact and are only a mediocre predictor of perceived quality. Many applications require more reliable assessment methods. This paper discusses issues in vision modeling for perceptual video quality assessment (PVQA). Its purpose is not to describe a particular model or system, but rather to summarize and to provide pointers to up-to-date knowledge of important characteristics of the human visual system, to explain how these characteristics may be incorporated in vision models for PVQA, to give a brief overview of the state-of-the-art and current efforts in this field, and to outline directions for future research.

Abstract — We present a watermarking procedure to embed copyright protection into digital video. Our watermarking procedure is scene-based and video dependent. It directly exploits spatial masking, frequency masking, and temporal properties to embed an invisible and robust watermark. The watermark consists of static and dynamic temporal components that are generated from a temporal wavelet transform of the video scenes. The resulting wavelet coefficient frames are modified by a perceptually shaped pseudorandom sequence representing the author. The noise-like watermark is statistically undetectable to thwart unauthorized removal. Furthermore, the author representation resolves the deadlock problem. The multiresolution watermark may be detected on single frames without knowledge of the location of the frames in the video scene. We demonstrate the robustness of the watermarking procedure to several video degradations and distortions. Index Terms — Copyright protection, data hiding, perceptual masking, video watermarking.

Data hiding is the process of encoding extra information in an image by making small modifications to its pixels. To be practical, the hidden data must be perceptually invisible yet robust to common signal processing operations. This paper introduces two schemes for hiding data in images. The techniques exploit perceptual masking properties to embed the data in an invisible manner. The first method employs spatial masking and data spreading to hide information by modifying image coefficients. The second method uses frequency masking to modify image spectral components. By using perceptual masking, we also increase robustness of the hidden information. Experimental results of data recovery after applying noise and JPEG coding to the hidden data are included. 1. INTRODUCTION We introduce two robust schemes to hide information, e.g., labels, into an image by modifying perceptually irrelevant portions of image data. By exploiting the human visual system (HVS), our techniques embed a large...

The rapid evolution of digital image manipulation and transmission techniques has created a pressing need for the protection of the intellectual property rights on images. A copyright protection method that is based on hiding an "invisible" signal, known as digital watermark, in the image is presented in this paper. Watermark casting is performed in the spatial domain by slightly modifying the intensity of randomly selected image pixels. Watermark detection does not require the existence of the original image and is carried out by comparing the mean intensity value of the marked pixels against that of the not marked pixels. Statistical hypothesis testing is used for this purpose. Pixel modifications can be done in such a way that the watermark is resistant to JPEG compression and lowpass filtering. This is achieved by minimizing the energy content of the watermark signal in higher frequencies while taking into account properties of the human visual system. A variation that generates im...

We propose a novel scheme to embed an invisible signature into an image to check image integrity and measure its distortion. The technique is based on the pseudo noise sequences and visual masking effects. The values of an image are modified by a pseudo noise signature which is shaped by the perceptual thresholds from masking effects. The method is robust and can gauge errors accurately up to half of the perceptual thresholds. It also readily identifies large image distortion. Experimental results after applying JPEG and white noise to the image are also reported. 1. INTRODUCTION We introduce a robust scheme to embed into an image an invisible pattern which is used to verify image integrity. Furthermore, the technique provides a distortion measurement indicating the amount of damage incurred upon an image. By exploiting limitations of the human visual system, the energy of the embedded pattern is maximized for robustness and yet is guaranteed to be perceptually invisible. Using mask...

AbstractÐIn this paper, we consider accelerated rendering of high quality walkthrough animation sequences along predefined paths. To improve rendering performance, we use a combination of a hybrid ray tracing and Image-Based Rendering (IBR) technique and a novel perception-based antialiasing technique. In our rendering solution, we derive as many pixels as possible using inexpensive IBR techniques without affecting the animation quality. A perception-based spatiotemporal Animation Quality Metric (AQM) is used to automatically guide such a hybrid rendering. The Image Flow (IF) obtained as a byproduct of the IBR computation is an integral part of the AQM. The final animation quality is enhanced by an efficient spatiotemporal antialiasing which utilizes the IF to perform a motioncompensated filtering. The filter parameters have been tuned using the AQM predictions of animation quality as perceived by the human observer. These parameters adapt locally to the visual pattern velocity. Index TermsÐWalkthrough animation, human perception, video quality metrics, motion-compensated filtering. æ 1

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This paper proposes a novel method for content-based watermarking based on feature points of an image. At each feature point, watermark is embedded after affine normalization according to the local characteristic scale and orientation. The characteristic scale is the scale at which the normalized scale-space representation of an image attains a maximum value, and the characteristic orientation is the angle of the principal axis of an image. By binding watermarking with the local characteristics of an image, resilience against affine transformations can be obtained. Experimental results show that the proposed method is robust against various image processing steps including affine transformations, cropping, filtering and JPEG compression.

The aim of this report is to provide background information on all topics in literature that are relevant to the development of a video watermarking method that will incorporate motion information in the embedding algorithm. First, a short introduction to digital video and digital image processing is given. Next, the following subjects are covered in more detail: video watermarking, the human visual system, video quality metrics and motion estimation. A general introduction to each subject is presented, followed by a discussion on several selected issues. Among these issues are: the working of the Philips watermark embedding and detection algorithm, the sensitivity to noise of the human visual system, subjective and objective metrics for image and video quality, the principles of motion estimation and a comparison of several motion estimators. Finally, specific issues regarding motion sensitive video watermarking algorithms are addressed, and a number of conclusions based on the preliminary literature study are discussed.