Computational imaging in multirotation cylinder lens based on precise angle estimation with principal component analysis

In the multirotation computational imaging system (MRCI), the rotation angle of the cylindrical lens is vital to the reconstruction results from the experimental data. However, the rotation angles of the cylindrical lens are hard to be measured directly and precisely. High-precision angle evaluation methods are urgently needed to improve the recovered images. This paper proposes an angle estimation scheme based on principal component analysis (PCA), which can calculate the rotation angle of the cylindrical lens efficiently and accurately. Its accuracy is an order of magnitude higher than that of the existing methods. The proposed method is also stable for the image reconstruction when testing complex samples and under defocusing case.