Table-based low-level image classification and compression system

Abstract

A system for classifying image elements comprising means for converting an image into a series of vectors and a hierarchical lookup table that classifies the vectors. The lookup table implements a pre-computed discrete cosine transform (DCT) to enhance classification accuracy. The hierarchical lookup table includes four stages: three of which constitute a preliminary section; the fourth stage constitutes the final section. Each stage has a respective stage table. The method for designing each stage table comprises a codebook design procedure and a table fill-in procedure. Codebook design for the preliminary stages strives to minimize a classification-sensitive proximity measure; codebook design for the final stage attempts to minimize Bayes risk of misclassification. Table fill-in for the first stage involves generating all possible input combinations, concatenating each possible input combination to define a concatenated vector, applying a DCT to convert the address vector to the spatial frequency domain, finding the closest first-stage codebook vector, and assigning to the address the index associated that codebook vector. Table fill-in for subsequent stages involves decoding each possible input combination to obtain spatial frequency domain vectors, applying an inverse DOC to convert the inputs to pixel domain vectors, concatenating the pixel domain vectors to obtain a higher dimension pixel domain vector, applying a DCT to obtain a spatial frequency domain vector, finding the closest same-stage codebook vector, and assigning the codebook vector index to the input combination.