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In-network processing is an appealing principle for resource conservation for sensor network applications. We propose a scheme to compress sensor array data in which one sensor has to send its readings to multiple neighbor sensors. This proposed scheme uses low-density parity-check code based Slepian-Wolf codes to compress these bit-planes extracted from wavelet coefficients with flexible rates, and each receiver uses the sum-product algorithm to decode the progressive transmission. A priori correlation statistic is not required in this scheme, and the reception rate of each receiver is close to conditional entropy with regard to the sender.