Although　multispectral　and　hyperspectral　imaging　acquisitions　are　applied　in　numerous　fields,　the　existing　spectral　imaging　systems　suffer　from　either　low　temporal　or　spatial　resolution.　In　this　study,　a　new　multispectral　imaging　system-camera　array　based　multispectral　super　resolution　imaging　system　(CAMSRIS)　is　proposed　that　can　simultaneously　achieve　multispectral　imaging　with　high　temporal　and　spatial　resolutions.　The　proposed　registration　algorithm　is　used　to　align　pairs　of　different　peripheral　and　central　view　images.　A　novel,　super-resolution,　spectral-clustering-based　image　reconstruction　algorithm　was　developed　for　the　proposed　CAMSRIS　to　improve　the　spatial　resolution　of　the　acquired　images　and　preserve　the　exact　spectral　information　without　introducing　false　information.　The　reconstructed　results　showed　that　the　spatial　and　spectral　quality　and　operational　efficiency　of　the　proposed　system　are　better　than　those　of　a　multispectral　filter　array　(MSFA)　based　on　different　multispectral　datasets.　The　PSNR　of　the　multispectral　super-resolution　images　obtained　by　the　proposed　method　were　respectively　higher　by　2.03　and　1.93　dB　than　those　of　GAP-TV　and　DeSCI,　and　the　execution　time　was　significantly　shortened　by　approximately　54.55　s　and　9820.19　s　when　the　CAMSI　dataset　was　used.　The　feasibility　of　the　proposed　system　was　verified　in　practical　applications　based　on　different　scenes　captured　by　the　self-built　system.