Product channel codes are proposed to protect progressively compressed and packetized images for noisy channels. Within packets, the product code uses the concatenation of a rate-compatible punctured convolutional code and an error detecting parity check code. Across packets, Reed-Solomon codes are used. Benefits include flexible choice of delay, adaptability of error protection level (i.e., unequal error protection), and scalable decoding complexity. The system outperforms the best known image coders for memoryless channels and performs well on fading channels.

Error protection for progressive image transmission over memoryless and fading channels

WebGIS (also known as web‐based GIS and Internet GIS) denotes a type of Geographic Information System (GIS), whose client is implemented in a Web browser. WebGISs have been developed and used extensively in real‐world applications. However, when such a complex web‐based system involves the dissemination of large volumes of data and/or massive user interactions, its performance can become an issue. In this paper, we first identify several major potential performance problems with WebGIS. Then, we discuss several possible techniques to improve the performance. These techniques include the use of pyramids and hash indices on the server side to handle large images. To resolve server‐side conflicts originating from concurrent massive access and user interactions, we suggest clustering and multithreading techniques. Multithreading is also used to break down the long sequential, layer‐based data access to concurrent data access on the client side. Caching is suggested as a means to enhance concurrent data access...

Performance‐improving techniques in web‐based GIS

Within distributed computing environments, access to very large geospatial datasets often suffers from slow or unreliable network connections. To allow users to start working with a partially delivered dataset, progressive transmission methods are a viable solution. While incremental and progressive methods have been applied successfully to the transmission of raster images over the World Wide Web, and, in the form of prototypes, of triangular meshes, the transmission of vector map datasets has lacked a similar attention. This paper introduces a solution to the progressive transmission of vector map data that allows users to apply analytical GIS methods to partially transmitted data sets. The architecture follows a client-server model with multiple map representations at the server side, and a thin client that compiles transmitted increments into a topologically consistent format. This paper describes the concepts, develops an architecture, and discusses implementation concerns.

Progressive Transmission of Vector Map Data over the World Wide Web

One method of transmitting wavelet based zerotree encoded images over noisy channels is to add channel coding without altering the source coder. A second method is to reorder the embedded zerotree bitstream into packets containing a small set of wavelet coefficient trees. We consider a hybrid mixture of these two approaches and demonstrate situations in which the hybrid image coder can outperform either of the two building block methods, namely on channels that can suffer packet losses as well as statistically varying bit errors.

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Combined forward error control and packetized zerotree wavelet encoding for transmission of images over varying channels

The progressive transmission of map data over World Wide Web provides the users with a self-adaptive strategy to access remote data. It not only speeds up the web transfer but also offers an efficient navigation guide in information acquisition. The key technology in this transmission is the efficient multiple representation of spatial data and pre-organization on server site. This paper aims at offering a new model for the multiple representations of vector data, called changes accumulation model, which considers the spatial representation from one scale to another as an accumulation of the set of changes. The difference between two consecutive representations is recorded in a linear order and through gradually addition or subtraction of “change patches” the progressive transmission is realized. As an example, the progressive transmission of area features based on this model is investigated in the project. The model is built upon the hierarchical decomposition of polygon into series of convex hulls or bounding rectangles and the progressive transmission is accomplished through component of the decomposed elements.

Progressive Transmission of Vector Data Based on Changes Accumulation Model

We propose a new maximum a posteriori (MAP) detector, without the need for explicit channel coding, to lessen the impact of communication channel errors on compressed image sources. The MAP detector exploits the spatial correlation in the compressed bitstream as well as the temporal memory in the channel to correct channel errors. We first present a technique for computing the residual redundancy inherent in a compressed grayscale image (compressed using VQ). The performance of the proposed MAP detector is compared to that of a memoryless MAP detector. We also investigate the dependence of the performance on memory characteristics of the Gilbert-Elliott channel as well as average channel error rate. Finally, we study the robustness of the proposed MAP detector's performance to estimation errors.

M. Azizoglu

Papers

Progressive transmission of images using MAP detection over channels with memory