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A novel speech enhancement system based on wavelet packet decomposition (WPD) is proposed. Noise level is estimated based on quantile in wavelet threshold domain. To handle colored and non-stationary noises, the universal thresholds are weighted by a time-frequency dependent nonlinear function. Two nonlinear weighting methods using temporal threshold variation and kernel smoothing are proposed. The weighted thresholds are smoothed and employed for wavelet shrinking with an adaptive factor to compress noise while preserving speech quality. The proposed system is evaluated and compared with other algorithms based on spectral subtraction via objective measures and subjective tests to demonstrate its superior performance.