Abstract: A client/server system serves imagery to users with speed, efficiency, and desirable functionality. Clients are allocated the means to determine the image data necessary to generate views on an image. The clients issue requests for such necessary image data to servers who service the requests and send requested image data to the clients who then generate the views. The system responds quickly to changes of views resulting form user actions such as panning or zooming by enabling clients to determine which image data is needed that has not already been served and requesting service of only that data. Clients are also enabled to issue requests to cancel service of data previously requested, but unserved and no longer needed.

Abstract: Image transformation and selective inverse transformation is implemented by performing DWT-based transformation on very large images using single or multi-CPU architectures without requiring large amounts of computer memory. The compression of a large image I(x,y) is accomplished by defining L=(log2(x)−log2(Filter_size)) DWT levels, each level Ln containing pre-allocated memory buffers sufficient to hold (Filter_size+1) lines of x/2n pixels length of DWT subbands. For each line of I(x,y), in a recursive fashion through levels L0 to Ln, the level DWT is computed and the level subband wavelets are compressed and stored or transmitted as required. The recursive DWT for each level of each line of I(x,y) results in a seamless DWT for I(x,y).

Abstract: Image transformation and selective inverse transformation is implemented by performing DWT-based transformation on very large images using single or multi-CPU architectures without requiring large amounts of computer memory. The compression of a large image I(x,y) is accomplished by defining L=(log2(x)−log2(Filter_size)) DWT levels, each level Ln containing pre-allocated memory buffers sufficient to hold (Filter_size+1) lines of x/2n pixels length of DWT subbands. For each line of I(x,y), in a recursive fashion through levels L0 to Ln, the level DWT is computed and the level subband wavelets are compressed and stored or transmitted as required. The recursive DWT for each level of each line of I(x,y) results in a seamless DWT for I(x,y).