In this work, the expectation of wavelet transform coefficients is used for estimating an image sharpness. It's based on the observation that the greater the probability of big detail coefficients, the more pixels appear sharply, and consequently, the sharper the image. Specifically, an input image is firstly decomposed into three directional sub-bands by a separable discrete wavelet transform. Then these directional sub-bands are viewed as three random variables, and their expectations are computed. Finally, The proposed sharpness index is the weighted sum of three expectations. The experiments show that, despite its simplicity, the proposed sharpness index is competitive with the current best-performance techniques for no-reference image sharpness estimation.