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This algorithm iteratively clusters data, updates centroids, and generates codewords to achieve compression. It dynamically adjusts cluster sizes and codewords to minimize error. Implements a split-and-merge approach for efficient compression.
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Reset • c_count、 sum • mse=0.0 Begin • Find data centroid • generate1’st codeword • level=1 t 1 >frame_num 0 Re-encode frame level level>codeword num 1 • Update cluster’s • sum • c_count • mse 1 • Split the largest • cluster into 2 clusters • level++ • generate two • codewords (left and • right shift by delta) • Check if any empty cluster? • level- - Compute new codewords t >frame_num 1 level < codeword_num? 0 no Re-encode frame yes • Split the largest • cluster into 2 clusters • level++ • generate two • codewords (left and • right shift by delta) yes Update cluster’s sum &c count • Check if any empty cluster? • level- - • Compute • mse • relative_error_cha nge • update last_mse= mse Compute new codewords While split=true or relative_error_change>ERROR yes • initialize • last_mse =0.0 no finish
