3075495
LOT-based adaptive image watermarking
A robust, invisible watermarking scheme is proposed for digital images, where the watermark is embedded using the block-based Lapped Orthogonal Transform (LOT). The embedding process follows a spread spectrum watermarking approach. In contrast to the use of transforms such as DCT, our LOT watermarking scheme allows larger watermark embedding energy while maintaining the same level of subjective invisibility. In particular, the use of LOT reduces block artifacts caused by the insertion of the watermark in a block-by-block manner, hence obtaining a better balance between invisibility and robustness. Moreover, we use a human visual system (HVS) model to adaptively adjust the energy of the watermark during embedding. In our HVS model, each block is categorized into one of four classes (texture, fine-texture, edge, and plain-area) by using a feature known as the Texture Masking Energy (TME). Blocks with edges are also classified according to the edge direction. The block classification is used to adjust the watermark embedding parameters for each block.
31701713
Wavelet image coding using cluster growing embedding
A novel embedded image coding method denoted as cluster growing embedding (CGE) is proposed in this paper. Similar to some of state-of-the-art wavelet image coding algorithms, CGE can encode images efficiently by exploiting the self-similarity across subbands in the wavelet domain. By utilizing morphological dilation, CGE forms significance clusters in each wavelet subband, and then exploits the parent-child relationship between subbands to encode the significance map information of one image. A salient new feature of CGE is that it tries to first encode the significance bits in the neighborhood of those already formed clusters. Therefore, CGE is more compatible to the functionality of embedded coding. Meanwhile, CGE is shown to be very suitable to the object-oriented coding framework along with the shape adaptive discrete wavelet transform (SA-DWT).
16336933
Adaptive Video Watermarking Scheme
In this paper, a new adaptive watermarking scheme for uncompressed and compressed video is presented. The proposed method embeds the watermark in DC components by quantizing DC coefficients to reference values, instead of embedding the watermark in AC components. To increase robustness and perceptual invisibility, adaptive quantization control strategy (AQCS) and error compensation strategy (ECS) are introduced. Experimental results demonstrate the proposed watermarking scheme is robust and invisible, and is feasible for real time system implementation.
7010436
Dynamic layer management in superpeer architectures
Superpeer unstructured P2P systems have been found to be very effective by dividing the peers into two layers, superlayer and leaf-layer, in which message flooding is only conducted among superlayer and all leaf-peers are represented by corresponding superpeers. However, current superpeer systems do not employ any effective layer management schemes, so the transient and low-capacity peers are allowed to act as superpeers. Moreover, the lack of an appropriate size ratio maintenance mechanism on superlayer to leaf-layer makes the system's search performance far from being optimal. We present one workload model aimed at reducing the weighted overhead of a network. Using our proposed workload model, a network can determine an optimal layer size ratio between leaf-layer and superlayer. We then propose a dynamic layer management algorithm, DLM, which can maintain an optimal layer size ratio and adaptively elect and adjust peers between superlayer and leaf-layer. DLM is completely distributed in the sense that each peer decides to be a superpeer or a leaf-peer independently without global knowledge. DLM could effectively help a superpeer P2P system maintain the optimal layer size ratio and designate peers with relatively long lifetime and large capacities as superpeers, and the peers with short lifetime and low capacities as leaf-peers under highly dynamic network situations. We demonstrate that the quality of a superpeer system is significantly improved under the DLM scheme by comprehensive simulations.
10288903
Sensor Planning with Non-linear Utility Functions
Sensor planning is concerned with when to sense and what to sense. We study sensor planning in the context of planning objectives that trade-off between minimizing the worst-case, expected, and best-case plan- execution costs. Sensor planning with these planning objectives is interesting because they are realistic and the frequency of sensing changes with the planning objective: more pessimistic decision makers tend to sense more frequently. We perform sensor planning by combining one of our techniques for planning with non-linear utility functions with an existing sensor-planning method. The resulting sensor-planning method is not only as easy to implement as the sensor-planning method that it extends but also (almost) as efficient. We demonstrate empirically how sensor plans change as the planning objective changes, using a common testbed for sensor planning.
7269331
Quadric Surface Extraction by Variational Shape Approximation
Based on Lloyd iteration, we present a variational method for extracting general quadric surfaces from a 3D mesh surface. This work extends the previous variational methods that extract only planes or special types of quadrics, i.e., spheres and circular cylinders. Instead of using the exact L2 error metric, we use a new approximate L2 error metric to make our method more efficient for computing with general quadrics. Furthermore, a method based on graph cut is proposed to smooth irregular boundary curves between segmented regions, which greatly improves the final results.
23466581
Object watermarks for digital images and video
Abstract The growth of new image technologies has created a need for techniques that can be used for copyright protection of digital images and video. One approach for copyright protection is to introduce an invisible signal, known as a digital watermark, into an image or video sequence. With the development of MPEG-4, frame-based approach has been migrating to object-based approach. Therefore, object-based watermarking schemes are needed. In this article, we propose a novel blind object watermarking scheme for images and video using shape adaptive-discrete wavelet transform (SA-DWT). To make the watermark robust and perceptual invisible, we embed it in the weighting mean of the wavelet blocks using the quantisation visual model based on the human visual system. Watermark detection is accomplished without the original, unwatermarked object by using statistical detection technique. Experimental results demonstrate that the proposed watermarking scheme is perceptual invisible and robust against many attacks such as lossy image/video compression (e.g. JPEG, JPEG2000 and MPEG-4), scaling, adding noise, filtering, D/A and A/D conversion, etc.