Adaptive Transform Coding as Constrained Vector Quantization
نویسندگان
چکیده
We investigate the application of local Principal Com ponent Analysis PCA to transform coding for xed rate image compression Local PCA transform coding adapts to di erences in correlations between signal components by partitioning the signal space into regions and compressing signal vectors in each region with a separate local transform coder Previous researchers optimize the signal space partition and transform coders independently and consequently underestimate the potential advantage of using adaptive transform coding meth ods We propose a new algorithm that concurrently optimizes the signal space partition and local transform coders This algorithm is simply a constrained version of the LBG algorithm for vector quantizer design Image compression experiments show that adaptive transform coders designed with our integrated algorithm compress an image with less distortion than previous related methods We saw im provements in compressed image signal to noise ratio of to dB compared to other tested adaptive methods and to dB compared to global PCA transform coding
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