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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 L.sub.n 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 L.sub.0 to L.sub.n, 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). The continual transmission or storage of compressed imagery occurs where it is desirable to transmit high volumes of imagery through limited transmission bandwidth or to limited disk storage, and is accomplished by compression and transmission or storage of each subband wavelet transformed image line using wavelet quantization and encoding before transmission or storage. The selective decompression of imagery is accomplished by a recursive reverse DWT reconstruction on the desired subset of each image line from the desired subset of lines from a compressed image stored on disk or received from continual transmission, for only as many levels as required to result in the required level of detail view for the image subset to be accessed or viewed.

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First Claim