14972252
Image coding with wavelet representations, edge information and visual masking
The wavelet transform provides a multiresolution representation of images. Edges, which are visually important, produce large coefficients across several scales in the wavelet transform domain. By tracking and predicting these edge coefficients across scales in the wavelet transform domain, we can greatly improve the compressed image quality with little degradation in compression ratio. This paper proposes a novel model-based edge tracking and prediction in the wavelet domain. It separates textures from edges and codes them differently. Edges are coded via an edge tracking and prediction, while textures are coded with either ordinary wavelet based image coding techniques or a "wavelet-like" filter bank which is similar to the tuning channels in the human vision system. The coding noise is then coded with a noise modelling. Visual masking models are also used to ensure the compressed image has little or almost no perceptual distortion.
964400
Arithmetic coding with dual symbol sets and its performance analysis
In this paper, we propose a novel adaptive arithmetic coding method that uses dual symbol sets: a primary symbol set that contains all the symbols that are likely to occur in the near future and a secondary symbol set that contains all other symbols. The simplest implementation of our method assumes that symbols that have appeared in the previously are highly likely to appear in the near future. It therefore fills the primary set with symbols that have occurred in the previously. Symbols move dynamically between the two symbol sets to adapt to the local statistics of the symbol source. The proposed method works well for sources, such as images, that are characterized by large alphabets and alphabet distributions that are skewed and highly nonstationary. We analyze the performance of the proposed method and compare it to other arithmetic coding methods, both theoretically and experimentally. We show experimentally that in certain contexts, e.g., with a wavelet-based image coding scheme that has appeared in the literature, the compression performance of the proposed method is better than that of the conventional arithmetic coding method and the zero-frequency escape arithmetic coding method.
32302991
Image coding by folding
We propose an image coding algorithm which employs data hiding techniques to "fold" an image into itself. Data hiding is a process of encoding extra information into a host image by making small modifications to its pixels. In our approach, an image is split into two parts of equal size: a host image and a residual image. The residual image is compressed into a bit stream and then embedded into the host image. The host image, which is 50% of the size of the original image, is coded using standard compression techniques. The embedded data does not increase the bit rate of the coded image. As a result, one may code only 50% pixels of the original image and still have perfect reconstruction. Experimental results indicate that the algorithm has a lot of potential in image coding.
5048240
Current state of the art, challenges and future directions for audio watermarking
Transparent data embedding algorithms embed binary streams in host multimedia signals. The embedded data is perceptually inaudible to maintain the quality of the source data. The embedded data can add features to the host multimedia signal or provide copyright protection. We review developments and requirements in transparent data embedding techniques for audio signals. We describe our latest audio embedding algorithm and include experimental results indicating robustness to low bit rate MPEG-Layer 3, AAC, and Dolby AC-3 coding. We conclude with a discussion of future research directions.
1450773
Multiresolution video watermarking using perceptual models and scene segmentation
We introduce a watermarking procedure to embed copyright protection into digital video. Our video dependent watermarking procedure directly exploits the 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. To generate the watermark, the resulting wavelet coefficient frames are modified by a perceptually shaped pseudo-random 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 distortions.
46211650
Data hiding for video-in-video
We introduce a scheme for hiding high bit-rate supplementary data, such as secondary video, into a digital video stream by directly modifying the pixels in the video frames. The technique requires no separate channel or bit interleaving to transmit the extra information. The data is invisibly embedded using a perception-based projection and quantization algorithm. The data hiding algorithm supports user-defined levels of accessibility and security. We illustrate our algorithm using examples of real-time video-in-video and speech-in-video. We also demonstrate the robustness of the data hiding procedure to video degradation and distortion, e.g., those that result from additive noise and compression.
15174288
Create a large-scale digital library for geo-referenced information
One of the most challenging research issues for geospatial collections is to develop techniques to support fuzzy, conceptbased, geographic information retrieval (GIR). Based on an artificial intelligence approach, this project presents a Geospatial Knowledge Representation System (GKRS) prototype system that integrates multiple multimedia (textual and image) knowledge sources to support concept-based GIR. Based on semantic network and neural network representations, GKRS loosely couples different knowledge sources and adopts spreading activation algorithms for concept-based knowledge inferencing. Both textual analysis and image processing techniques have been employed to create textual and visual geographical knowledge structures. This project suggests a framework for developing a complete GKRS-based system and describes in detail the prototype.
17379626
Validating a geographical image retrieval system
This paper summarizes a prototype geographical image retrieval system that demonstrates how to integrate image processing and information analysis techniques to support large-scale content-based image retrieval. By using an image as its interface, the prototype system addresses a troublesome aspect of traditional retrieval models, which require users to have complete knowledge of the low-level features of an image. In addition we describe an experiment to validate the performance of this image retrieval system against that of human subjects in an effort to address the scarcity of research evaluating performance of an algorithm against that of human beings. The results of the experiment indicate that the system could do as well as human subjects in accomplishing the tasks of similarity analysis and image categorization. We also found that under some circumstances texture features of an image are insufficient to represent a geographic image. We believe, however, that our image retrieval system provides a promising approach to integrating image processing techniques and information retrieval algorithms.
38129543
Enhanced Verification-Based Decoding for Packet-Based LDPC Codes over Wireless Channels
In this paper, we apply the enhanced verification-based decoding algorithm (EVA) for packet-based LDPC codes over wireless channels. Compared with the verification algorithm (VA) in the literature, the EVA algorithm enhances the verification condition thereby reducing the likelihood of false verification. The wireless channels in simulations are modeled by binary symmetric channel (BSC) and Gilbert-Elliott (GE) channel. The numerical results indicate the proposed algorithm gives a superior performance but with only moderate computation increase compared with VA. For example, when the bit error probability is less than 10-3 in bad state of GE channel, the EVA reduces the frame error rate (FER) by one order with less than 35% complexity increase compared with VA.
12630328
Creating a large-scale content-based airphoto image digital library
This paper describes a content-based image retrieval digital library that supports geographical image retrieval over a testbed of 800 aerial photographs, each 25 megabytes in size. In addition, this paper also introduces a methodology to evaluate the performance of the algorithms in the prototype system. There are two major contributions: we suggest an approach that incorporates various image processing techniques including Gabor filters, image enhancement and image compression, as well as information analysis techniques such as the self-organizing map (SOM) into an effective large-scale geographical image retrieval system. We present two experiments that evaluate the performance of the Gabor-filter-extracted features along with the corresponding similarity measure against that of human perception, addressing the lack of studies in assessing the consistency between an image representation algorithm or an image categorization method and human mental model.
2946583
Visualizing a computer mediated communication (CMC) process to facilitate knowledge management
The archive of a computer-mediated communication (CMC) process contains knowledge shared and implicit information about participants' behavior patterns during discussion. However, most CMC systems focus only on organizing the content of discussions. On the other hand, the social visualization research has developed techniques to depict human behaviors during a process of CMC but has not been integrated in any organizational memory system yet. In addition, the impacts of the graphical representations created by social visualization techniques have seldom been studied. The dissertation thus proposes a two-phase research to address those issues. The first phase proposes a prototype system that integrates a social visualization technique with various information analysis technologies to graphically summarize both the content and behavior of a CMC process. The second phase proposes to adopt the "de-featuring" approach used by previous interface evaluation studies to evaluate how the graphical interface developed affects users' information acquisition and evaluation process.