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Transmitting the face image data through wireless fading channels have been widely used for face recognition and automatic surveillance applications and many techniques can be used to do that. However, due to the noise and wireless fading channels, the perfect recovery cannot be achieved. So there are needs to use efficient techniques for image recovery and denoising. The wavelet and contourlet transforms along with some denoising schemes such as Hard thresholding to estimate the true coefficients from noisy ones have been already used. In this paper, we propose to use Wavelet-Based Contourlet Transform (WBCT) comprised with Block thresholding to more efficiently denoise and recovery transmitted face images. The simulation results show that for general face images the WBCT is quite competitive to the contourlet and wavelet transforms in the SNR sense and in visual aspects.