Conventional electro-optical and infrared (EO/IR) systems (i.e., active, passive, multiband and hyperspectral) capture an image by optically focusing the incident light at each of the millions of pixels in a focal plane array. The optics and the focal plane are designed to efficiently capture desired aspects (like spectral content, spatial resolution, depth of focus, polarization, etc.) of the scene. Computational imaging refers to image formation techniques that use digital computation to recover an image from an appropriately multiplexed or coded light intensity of the scene. In this case, the desired aspects of the scene can be selected at the time of image reconstruction which allows greater flexibility of the EO/IR system. Compressive sensing involves capturing a smaller number of specifically designed measurements from the scene to computationally recover the image or task specific scene information. Compressive sensing has the potential to acquire an image with equivalent information content to a large format array while using smaller, cheaper, and lower bandwidth components. More significantly, the data acquisition can be sequenced and designed to capture task specific and mission relevant information guided by the scene content with more flexibility. However, the benefits of compressive sensing and computational imaging do not come without compromise. NATO SET-232 has undertaken the task of investigating the promise of computational imaging and compressive sensing for EO/IR systems. This paper presents an overview of the ongoing joint activities by NATO SET-232, current computational imaging and compressive sensing technologies, limitations of the design trade space, algorithm and conceptual design considerations, and field performance assessment and modeling.