Since the heat noise of Synthetic Aperture Radar（SAR） imaging system and sea clutter severely affect the performance of automatic targets detection in SAR images

removing noise and homogenizing sea clutter in SAR images to improve performance of targets detection is a challenge for researchers.Considering the noise power exists small scale and the boundaries of target signal exist cross-scale in SAR images

we propose a novel scheme which enhances signal and removes noise based on multiscale products method to detect ship targets.The algorithm applies wavelet transform to SAR image and enhances ship signal and homogenizes background clutter of SAR images in wavelet domain using multiscale products.And then detects ship targets in enhanced SAR images.ERS SAR images are used to test our detection algorithm.The simulating results show that the new detector improves detection performance when it is to compare the two-parameter constant false alarm detector and the detection algorithm based on K-distribution.To estimate the efficacy of our enhancement algorithm

we compute computation complexity of the algorithm and a popular enhancement algorithm which is based on wavelet soft threshold.It shows that our algorithm is easier to implement using hardware.The two enhancement algorithms are applied to SAR image ship targets detection.The detected results show that the detection performance of our algorithm is better than the later.