Abstract: A method for optimization of alignment of pixels of X different types on a sensor array for the performance of N different camera tasks, where X and N are integers greater than 1, includes obtaining an output of each of the X types of pixel on the sensor array for an input image; evaluating the quality of the output for each of the N different camera tasks; and obtaining an optimal pixel alignment pattern by adjustment of a potential pixel alignment pattern with respect to performance of the N different camera tasks subject to a user-determined balance of priorities among the N different camera tasks.

Abstract: Information about an image's source camera model is important knowledge in many forensic investigations. In this paper the system(s) pro-pose a system that compares two image patches to determine if they were captured by the same camera model. To do this, the system(s) first train a CNN based feature extractor to output generic, high level features which encode information about the source camera model of an image patch. Then, the system(s) learn a similarity measure that maps pairs of these features to a score indicating whether the two image patches were captured by the same or different camera models. The system(s) show that the proposed system accurately determines if two patches were captured by the same or different camera models, even when the camera models are unknown to the investigator. The system(s) also demonstrate the utility of this approach for image splicing detection and localization.