We present a compressive spectral polarization imager based on a prism which is rotated to different angles as the measurement shots are taken, and a colored detector with a micropolarizer array. The prism shears the scene along one spatial axis according to its wavelength components. The scene is then projected to different locations on the detector as measurement shots are taken. Composed of 0°, 45°, 90°, 135° linear micropolarizers, the pixels of the micropolarizer array matched to that of the colored detector, thus the first three Stokes parameters of the scene are compressively sensed. The four dimensional (4D) data cube is thus projected onto the two dimensional (2D) FPA. Designed patterns for the micropolarizer and the colored detector are applied so as to improve the reconstruction problem. The 4D spectral-polarization data cube is reconstructed from the 2D measurements via nonlinear optimization with sparsity constraints. Computer simulations are performed and the performance of designed patterns is compared with random patterns.