Abstract
An efficient way to store and retrieve digitized chart images using a lossy vector quantization (VQ) compression technique is presented. A VQ codebook is located using the fast pairwise nearest neighbor (PNN) clustering algorithm. A k-d tree data structure is used for efficient image compression. Some unique features of this approach are that compressed files use a predictable amount of storage, and can be decompressed quickly for display on equipment ranging from portable personal computers to advanced graphics workstations. The method also applies to panchromatic and multispectral satellite imagery. In this application, digitized chart images with compression ratios of 24:1 exhibited good quality. In certain applications, even higher compression ratios are feasible.
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