Reginald L. Lagendijk

Watermarking digital image and video data. A state-of-the-art overview

The authors begin by discussing the need for watermarking and the requirements. They go on to discuss digital watermarking techniques based on correlation and techniques that are not based on correlation.

Iterative methods for image deblurring

The authors discuss the use of iterative restoration algorithms for the removal of linear blurs from photographic images that may also be assumed to be degraded by pointwise nonlinearities such as film saturation and additive noise. Iterative algorithms allow for the incorporation of various types of prior knowledge about the class of feasible solutions, can be used to remove nonstationary blurs, and are fairly robust with respect to errors in the approximation of the blurring operator. Special attention is given to the problem of convergence of the algorithms, and classical solutions such as inverse filters, Wiener filters, and constrained least-squares filters are shown to be limiting solutions of variations of the iterations. Regularization is introduced as a means for preventing the excessive noise magnification that is typically associated with ill-conditioned inverse problems such as the deblurring problem, and it is shown that noise effects can be minimized by terminating the algorithms after a finite number of iterations. The role and choice of constraints on the class of feasible solutions are also discussed. >

Optimal differential energy watermarking of DCT encoded images and video

This paper proposes the differential energy watermarking (DEW) algorithm for JPEG/MPEG streams. The DEW algorithm embeds label bits by selectively discarding high frequency discrete cosine transform (DCT) coefficients in certain image regions. The performance of the proposed watermarking algorithm is evaluated by the robustness of the watermark, the size of the watermark, and the visual degradation the watermark introduces. These performance factors are controlled by three parameters, namely the maximal coarseness of the quantizer used in pre-encoding, the number of DCT blocks used to embed a single watermark bit, and the lowest DCT coefficient that we permit to be discarded. We follow a rigorous approach to optimizing the performance and choosing the correct parameter settings by developing a statistical model for the watermarking algorithm. Using this model, we can derive the probability that a label bit cannot be embedded. The resulting model can be used, for instance, for maximizing the robustness against re-encoding and for selecting adequate error correcting codes for the label bit string.

Automated high-level movie segmentation for advanced video-retrieval systems

We present a newly developed strategy for automatically segmenting movies into logical story units. A logical story unit can be understood as an approximation of a movie episode, which is a high-level temporal movie segment, characterized either by a single event (dialog, action scene, etc.) or by several events taking place in parallel. Since we consider a whole event and not a single shot to be the most natural retrieval unit for the movie category of video programs, the proposed segmentation is the crucial first step toward a concise and comprehensive content-based movie representation for browsing and retrieval purposes. The automation aspect is becoming increasingly important with the rising amount of information to be processed in video archives of the future. The segmentation process is designed to work on MPEG-DC sequences, where we have taken into account that at least a partial decoding is required for performing content-based operations on MPEG compressed video streams. The proposed technique allows for carrying out the segmentation procedure in a single pass through a video sequence.

Regularized iterative image restoration with ringing reduction

Linear space-invariant image restoration algorithms often introduce ringing effects near sharp intensity transitions. It is shown that these artifacts are attributable to the regularization of the ill-posed image restoration problem. Two possible methods to reduce the ringing effects in restored images are proposed. The first method incorporates deterministic a priori knowledge about the original image into the restoration algorithm. The second method locally regulates the severity of the noise magnification and the ringing phenomenon, depending on the edge information in the image. A regularized iterative image restoration algorithm is proposed in which both ringing reduction methods are included by making use of the theory of the projections onto convex sets and the concept of norms in a weighted Hilbert space. Both the numerical performance and the visual evaluation of the results are improved by the use of ringing reduction. >

Noise reduction filters for dynamic image sequences: a review

In this paper, a thorough review is presented of noise reduction filters for digital image sequences. Detailed descriptions of several spatiotemporal and temporal noise reduction algorithms are provided. To aid in comparing between these different algorithms, we classify them based on their support (i.e., 3-D or 1-D filter) and whether or not motion compensation is employed. Several algorithms from each of the four categories are implemented and tested on real sequences degraded to various signal-to-noise ratios. These experimental results are discussed and analyzed to determine the overall advantages and disadvantages of the four general classifications, as well as, the individual filters. >

Encrypted signal processing for privacy protection: Conveying the utility of homomorphic encryption and multiparty computation

In recent years, signal processing applications that deal with user-related data have aroused privacy concerns. For instance, face recognition and personalized recommendations rely on privacy-sensitive information that can be abused if the signal processing is executed on remote servers or in the cloud. In this tutorial article, we introduce the fusion of signal processing and cryptography as an emerging paradigm to protect the privacy of users. While service providers cannot access directly the content of the encrypted signals, the data can still be processed in encrypted form to perform the required signal processing task. The solutions for processing encrypted data are designed using cryptographic primitives like homomorphic cryptosystems and secure multiparty computation (MPC).

Maximum likelihood image and blur identification: a unifying approach

A number of different algorithms have recently been proposed to identify the image and blur model parameters from an image that is

Video segmentation by MAP labeling of watershed segments

This paper addresses the problem of spatio-temporal segmentation of video sequences. An initial intensity segmentation method (watershed segmentation) provides a number of initial segments which are subsequently labeled, with a known number of labels, according to motion information. The label field is modeled as a Markov random field where the statistical spatial and and temporal interactions are expressed on the basis of the initial watershed segments. The labeling criterion is the maximization of the conditional a posteriori probability of the label field given the motion hypotheses, the estimate of the label field of the previous frame, and the image intensities. For the optimization, an iterative motion estimation-labeling algorithm is proposed and experimental results are presented.

Motion Analysis and Image Sequence Processing

Preface. 1. Hierarchical Model-Based Motion Estimation P. Anandan, J.R. Bergen, K.J. Hanna, R. Hingorani. 2. An Estimation Theoretic Perspective on Image Processing and the Calculation of Optical Flow T.M. Chin, M.R. Luettgen, W.C. Karl, A.S. Willsky. 3. Estimation of 2-D Motion Fields from Image Sequences with Application to Motion-Compensated Processing J. Konrad, E. Dubois. 4. Edge-Based 3-D Camera Motion Estimation with Application to Video Coding E. Zakhor, F. Lari. 5. Motion Compensation: Visual Aspects, Accuracy, and Fundamental Limits B. Girod. 6. Motion Field Estimators and their Application to Image Interpolation S. Tubaro, F. Rocca. 7. Subsampling of Digital Image Sequences using Motion Information R.A.F. Belfor, R.L. Lagendijk, J. Biemond. 8. Image Sequence Coding using Motion-Compensated Subband Decomposition A. Nicoulin, M. Mattavelli, W. Li, A. Basso, A. Popat, M. Kunt. 9. Vector Quantization for Video Data Compression R.M. Mersereau, M.J.T. Smith, C.S. Kim, F. Kossentini, K.K. Truong. 10. Model-Based Image Sequence Coding M. Buck, N. Diehl. 11. Human Facial Motion Analysis and Synthesis with Applications to Model-Based Coding K. Aizawa, C.s. Choi, H. Harashima, T.S. Huang. 12. Motion Compensated Spatiotemporal Kalman Filtering J.W. Woods, J. Kim. 13. Multiframe Wiener Restoration of Image Sequences M.K. Ozkan, M.I. Sezan, A.T. Erdem, A.M. Tekalp. 14. 3-D Median Structures for Image Sequence Filtering and Coding T. Viero, Y. Neuvo. 15. Video Compression for Digital ATV Systems J.G. Apostolopoulos, J.S. Lim. Index.