The goal of this paper is to improve the watermarking performance using the following two methods; watermark estimation and low density parity check (LDPC) codes. For a blind watermark decoding, the power of a host image, which is hundreds times greater than the watermark power, is the main noise source. Therefore, a technique that can reduce the effect of the power of the host image to the detector is required. To this end, we need to estimate watermark from the watermarked image. In this paper, the watermark estimation is done by an adaptive estimation method with the generalized Gaussian distribution modeling of sub-band coefficients in the wavelet domain. Since the watermark capacity as well as the error rate can be improved by adopting optimum decoding principles and error correcting codes (ECC), we employ the LDPC codes for the decoding of the estimated watermark. Also, in LDPC codes, the knowledge about the noise power can improve the error correction capability. Simulation results demonstrate the superior performance of the proposed algorithm comparing to LDPC decoding with other estimation-based watermarking algorithms.