We introduce a new method for color image sharpening based on S-CIELAB extension. S-CIELAB involves a series of smoothing spatial filters in the opponent color space to approximate the contrast sensitivity functions of the human vision system. The filters are linear combinations of Gaussian masks. We combine these spatial filters with the Laplacian operator in each opponent channel to obtain the sharpened image. The Laplacian of the smoothed components can be simplified by introducing the Laplacian of Gaussian (LoG) operator. Alternatively, the LoG operator can be approximated by the difference of Gaussians (DoG) operator. Moreover, the use of DoG operator can be justified since it is used to model the receptive field performance in early human vision. The resulting image is subtracted from the image in each opponent channel and then back transformed to the device independent representation space (XYZ) to obtain the final sharpened image.The method is tested and applied to digital color images. The results are compared with other results obtained by applying the LoG operator to the intensity channel only (keeping the chromatic components unchanged), or by applying the simple Laplacian to the image components in two representations (opponent color space and RGB).