Pina Marziliano

A no-reference perceptual blur metric

We present a no-reference blur metric for images and video. The blur metric is based on the analysis of the spread of the edges in an image. Its perceptual significance is validated through subjective experiments. The novel metric is near real-time, has low computational complexity and is shown to perform well over a range of image content. Potential applications include optimization of source coding, network resource management and autofocus of an image capturing device.

Perceptual Blur and Ringing Metrics: Application to JPEG2000

We present a full- and no-reference blur metric as well as a full-reference ringing metric. These metrics are based on an analysis of the edges and adjacent regions in an image and have very low computational complexity. As blur and ringing are typical artifacts of wavelet compression, the metrics are then applied to JPEG2000 coded images. Their perceptual significance is corroborated through a number of subjective experiments. The results show that the proposed metrics perform well over a wide range of image content and distortion levels. Potential applications include source coding optimization and network resource management.

Sparse Sampling of Signal Innovations

Sparse sampling of continuous-time sparse signals is addressed. In particular, it is shown that sampling at the rate of innovation is possible, in some sense applying Occams razor to the sampling of sparse signals. The noisy case is analyzed and solved, proposing methods reaching the optimal performance given by the Cramer-Rao bounds. Finally, a number of applications have been discussed where sparsity can be taken advantage of. The comprehensive coverage given in this article should lead to further research in sparse sampling, as well as new applications. One main application to use the theory presented in this article is ultra-wide band (UWB) communications.

A hybrid watermarking scheme for H.264/AVC video

A novel H.264/AVC watermarking method is proposed in this paper. By embedding the robust watermark into DCT domain and the fragile watermark into motion vectors respectively, the proposed method can jointly achieve both copyright protection and authentication. Our scheme outperforms other video watermarking schemes on higher watermarking capacity especially in lower compression bit-rates. Furthermore, being well aligned with Lagrangian optimization for mode choice featured in H.264/AVC, the proposed scheme only introduces small distortions into the video content. Experimental results also demonstrate that the proposed solution is very computationally efficient during watermark extraction.

Robust Video Watermarking of H.264/AVC

A robust video watermarking scheme of the state-of-the-art video coding standard H.264/AVC is proposed in this brief. 2-D 8-bit watermarks such as detailed company trademarks or logos can be used as inconvertible watermark for copyright protection. A grayscale watermark pattern is first modified to accommodate the H.264/AVC computational constraints, and then embedded into video data in the compressed domain. With the proposed method, the video watermarking scheme can achieve high robustness and good visual quality without increasing the overall bit-rate. Experimental results show that our algorithm can robustly survive transcoding process and strong common signal processing attacks, such as bit-rate reduction, Gaussian filtering and contrast enhancement

A new semi-fragile image watermarking with robust tampering restoration using irregular sampling

This paper presents a semi-fragile watermarking method for the automatic authentication and restoration of the content of digital images. Semi-fragile watermarks are embedded into the original image, which reflect local malicious tampering on the image. When tampered blocks are detected, the restoration problem is formulated as an irregular sampling problem. These blocks are then reconstructed, making use of the information embedded in the same watermarked image, through iterative projections onto convex sets. In contrast to previous methods, the restoration process is robust to common image processing operations such as lossy transcoding and image filtering. Simulation results showed that the scheme keeps the probability of false alarm to a minimum while maintaining the data integrity of the restored images.

Reconstruction of irregularly sampled discrete-time bandlimited signals with unknown sampling locations

The purpose of this paper is to develop methods that can reconstruct a bandlimited discrete-time signal from an irregular set of samples at unknown locations. We define a solution to the problem using first a geometric and then an algebraic point of view. We find the locations of the irregular set of samples by treating the problem as a combinatorial optimization problem. We employ an exhaustive method and two descent methods: the random search and cyclic coordinate methods. The numerical simulations were made on three types of irregular sets of locations: random sets; sets with jitter around a uniform set; and periodic nonuniform sets. Furthermore, for the periodic nonuniform set of locations, we develop a fast scheme that reduces the computational complexity of the problem by exploiting the periodic nonuniform structure of the sample locations in the DFT.

Automatic segmentation of the choroid in enhanced depth imaging optical coherence tomography images

Enhanced Depth Imaging (EDI) optical coherence tomography (OCT) provides high-definition cross-sectional images of the choroid in vivo, and hence is used in many clinical studies. However, the quantification of the choroid depends on the manual labelings of two boundaries, Bruch’s membrane and the choroidal-scleral interface. This labeling process is tedious and subjective of inter-observer differences, hence, automatic segmentation of the choroid layer is highly desirable. In this paper, we present a fast and accurate algorithm that could segment the choroid automatically. Bruch’s membrane is detected by searching the pixel with the biggest gradient value above the retinal pigment epithelium (RPE) and the choroidal-scleral interface is delineated by finding the shortest path of the graph formed by valley pixels using Dijkstra’s algorithm. The experiments comparing automatic segmentation results with the manual labelings are conducted on 45 EDI-OCT images and the average of Dice’s Coefficient is 90.5%, which shows good consistency of the algorithm with the manual labelings. The processing time for each image is about 1.25 seconds.

Sampling and Reconstruction of Sparse Signals in Fractional Fourier Domain

Sampling theory for continuous time signals which have a bandlimited representation in fractional Fourier transform (FrFT) domain-a transformation which generalizes the conventional Fourier transform-has blossomed in the recent past. The mechanistic principles behind Shannons sampling theorem for fractional bandlimited (or fractional Fourier bandlimited) signals are the same as for the Fourier domain case i.e. sampling (and reconstruction) in FrFT domain can be seen as an orthogonal projection of a signal onto a subspace of fractional bandlimited signals. As neat as this extension of Shannons framework is, it inherits the same fundamental limitation that is prevalent in the Fourier regime-what happens if the signals have singularities in the time domain (or the signal has a nonbandlimited spectrum)? In this paper, we propose a uniform sampling and reconstruction scheme for a class of signals which are nonbandlimited in FrFT sense. Specifically, we assume that samples of a smoothed version of a periodic stream of Diracs (which is sparse in time-domain) are accessible. In its parametric form, this signal has a finite number of degrees of freedom per unit time. Based on the representation of this signal in FrFT domain, we derive conditions under which exact recovery of parameters of the signal is possible. Knowledge of these parameters leads to exact reconstruction of the original signal.

Fragile Watermarking Based on Encoding of the Zeroes of the

In this paper, a new fragile watermarking method for digital image authentication is proposed based on the zero locations of the z-transform. The z-transform domain is a new transform space for fragile watermark embedding. Our watermarking method is designed by exploiting the sensitivity of the positions of the zeroes of the z-transform around the unit circle to any change made on the host image. The watermarking system can localize the portions of a watermarked image that have been tampered with with high accuracy. In addition, the newly proposed scheme is more secure than normal least-significant bits-based fragile watermarking techniques. Experimental results as well as the theoretical analysis demonstrated the fragility and accuracy of the new method.