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Chromatic aberration is the phenomenon where light of different wavelengths fail to converge at the same position on the focal plane. There are two kinds of chromatic aberration: longitudinal aberration causes different wavelengths to focus at different distances from the lens while lateral aberration is attributed to different wavelengths focusing at different positions on the sensor. In this paper, we estimate the parameters of lateral chromatic aberration by maximizing the mutual information between the corrected R and B channels with the G channel. The extracted parameters are then used as input features to a SVM classifier for identifying source cell phone of images. By considering only a certain part of the image when estimating the parameters, we reduce the runtime complexity of the algorithm dramatically while preserving the accuracy at a high level.