Color image quality assessment (CIQA) is a hot spot in researching image quality assessment (IQA). Chromatic information has a certain effect on the human visual system (HVS). Based on the conversion of RGB images to another color space YIQ, we obtain SSIM and GSSIM of the color image (C-SSIM and C-GSSIM) by extending the structural similarity index (SSIM) and gradient-based SSIM (GSSIM) of the grayscale image. In addition, considering HVS as a complex nonlinear system, two general pooling strategies are used to describe HVS characteristics to improve the evaluation effect of C-SSIM, C-GSSIM and feature similarity of the color image (C-FSIM). The numerical results, performed in TID2013 image database, demonstrate that C-SSIM, C-GSSIM and C-FSIM based on the general mean pooling strategy can effectively improve the accuracy of IQA.