Guided image filtering is an effective edge-preserving smoothing technique. However

because the regularization parameter and amplification factor of the detail layer are fixed instead of content adaptive

the halo effects near the edges and noise in the background may be incurred

which will degrade the quality of the output images further. In this paper

an improved edge-aware weighting is first proposed to preserve the edges more accurately and reduce the halo effects. Then

the amplification factor of the detail layer is calculated in a gradient-directed way for boosting the details while suppressing the noise. Experimental results on the low-dose CT images with heavy noise and small details show that the proposed method can reduce the halo effects and attenuate the noise while enhancing the contrast efficiently. The visual quality of the output images meets the requirement of the clinical diagnosis.