This paper highlights color component features that improve high-resolution satellite (HRS) images retrieval. Color component correlation across image lines and columns is used to define a revised color space. It is designed to simultaneously take both color and neighborhood information. From this space, color descriptors, namely rotation invariant uniform local binary pattern, histogram of gradient, and a modified version of local variance are derived through dual-tree complex wavelet transform (DT-CWT). A new color descriptor called smoothed local variance (SLV) using an edge-preserving smoothing filter is introduced. It is intended to offer an efficient way to represent texture/structure information using an invariant to rotation descriptor. This descriptor takes advantage of DT-CWT representation to enhance the retrieval performance of HRS images. We report an evaluation of the SLV descriptor associated with the new color space using different similarity distances in our content-based image retrieval scheme. We also perform comparison with some standard features. Experimental results show that SLV descriptor allied to DT-CWT representation outperforms the other approaches.