Content-based image retrieval has become a significant research topic because of the proliferation of video and image data in digital form. Increased bandwidth availability to access the Internet in the near future will allow the users to search for and browse through video and image databases located at remote sites. Therefore fast retrieval of images from large databases is an important problem that needs to be addressed. The disadvantages of the traditional color image retrieval based on color histogram are not considering the color spatial distribution and high complexity of computation. And what's more, the retrieval results with the condition of noise image are not good as expected. So an efficient color image retrieval technique based on multi-features of bit-plane is proposed in this paper. Firstly, according to the noise attack characteristic, the significant bit-planes are extracted from the color image. Secondly, the weighted color histograms are extracted from the significant bit-planes as color feature, and the space information entropy of every significant bit-plane is computed as spatial feature. Finally, the similarity between color images is computed by using a combined index based on color feature and spatial feature. Experimental results show that the proposed color image retrieval is more accurate and efficient in retrieving the user-interested images. Especially, it can retrieve the noise (including fuzzy, sharpen, and illumination, etc) image effectively.