Complex wavelets can provide both shift invariance and good directional selectivity

which are lack in the traditional wavelet transform

but can not satisfy the condition of perfect reconstruction. Dual tree complex wavelet transform (DTCWT)

which employs a dual tree of wavelet filters to obtain the real and imaginary parts of complex wavelet coefficients

can solve this problem. In this paper

the principle of DTCWT is discussed

and the directional characteristics of the twelve high frequency sub bands after DTCWT are studied. Based on the good directional characteristics of DTCWT

we propose a directional filtering method for enhancement of curve like texture images. Image filtering by using this method

the information of the local main direction in each sub band of wavelet transform domain is reserved

and the noise distributed in other directions is removed. This method is proven to be not only less complex

since it avoids the frequency and statistical estimations on characteristics of both the signal and noise

but also on better directional selectivity than real wavelet transform. The experimental results on texture image enhancement demonstrate that this method is more efficient and also more suitable for complicated textures images.