In this paper, we investigate the potential application of the multispectral filter array (MSFA) techniques in multispectral imaging for reasons like low cost, exact registration, and strong robustness. In both human and many animal visual systems, different types of photoreceptors are organized into mosaic patterns. This behavior has been emulated in the industry to develop the so-called color filter array (CFA) in the manufacture of digital color cameras. In this way, only one color component is measured at each pixel, and the sensed image is a mosaic of different color bands. We extend this idea to multispectral imaging by developing generic mosaicking and demosaicking algorithms. The binary tree-driven MSFA design process guarantees that the pixel distributions of different spectral bands are uniform and highly correlated. These spatial features facilitate the design of the generic demosaicking algorithm based on the same binary tree, which considers three interrelated issues: band selection, pixel selection and interpolation. We evaluate the reconstructed images from two aspects: better reconstruction and better target classification. The experimental results demonstrate that the mosaicking and demosaicking process preserves the image quality effectively, which further supports that the MSFA technique is a feasible solution for multispectral cameras.