Optimal rate allocation for joint compression and classification in JPEG 2000
Ali Tabesh, Michael W. Marcellin, Mark Allen Neifeld · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2004
We present a framework for optimal rate allocation to image subbands to minimize the distortion in the joint compression and classification of JPEG2000-compressed images. The distortion due to compression is defined as a weighted linear combination of the mean-square error (MSE) and the loss in the Bhattacharyya distance (BD) between the class-conditional distributions of the classes. Lossy compression with JPEG2000 is accomplished via deadzone uniform quantization of wavelet subbands. Neglecting the effect of the deadzone, expressions are derived for the distortion in the case of two classes with generalized Gaussian distributions (GGDs), based on the high-rate analysis of Poor. In this regime, the distortion function takes the form of a weighted MSE (WMSE) function, which can be minimized using reverse water-filling. We present experimental results based on synthetic data to evaluate the efficacy of the proposed rate allocation scheme. The results indicate that by varying the weight factor balancing the MSE and the Bhattacharyya distance, we can control the trade-off between these two terms in the distortion function.