Noise map for CT images have been estimated by generalizing the prior art even-and-odd views approach. One example is to estimate a noise map from images reconstructed from three sets of independent views. A second example is to estimate a noise map from images reconstructed by using two sets of correlated views. A third example is to estimate a noise map from noise map from two images reconstructed from two sets of independent views while the number of views in each set is unequal. Physical phantom data were employed to validate our proposed noise map estimation methods. In comparison to the existing method, our alternative methods yield reasonably accurate noise map estimation.