Optical sectioning through the numerical reconstruction of digital holographic data with low diffraction noise is the key process for understanding the structure of a recorded three-dimensional object. Recently, this has been enabled by compressive holography, by virtue of sparse signal processing. However, interpretation of the object signal domain has been limited to predefined domains, such as spatial, discrete cosine transform, and wavelet transform domains. We propose a reconstruction technique of compressive Fresnel holographic data using an overcomplete dictionary learned from natural images to enhance the axial resolution of the sectional images. The redundant (overcomplete) dictionary gives sparser and more flexible solutions for representing the two-dimensional images compared to predefined transforms. We provide simulation results to verify the feasibility of our proposed method.
An elemental image of the pre-distortion image in the off-axis integral floating system using a concave mirror is
generated. The concave mirror can be adopted as the floating device to improve the optical efficiency. The image
deformation due to the tilting axis of the concave mirror is analyzed to generate the pre-distortion image process. In this
paper, we calculate the image deformation in the off-axis structure of the concave mirror using the geometrical optics.
Using the simulation, the pre-distortion image is generated to compensate the 3D image. And the elemental image is
generated for the pre-distortion integrated image, which can be projected to the floating 3D image to resolve the image
deformation. The experiments of the off-axis integral floating are presented to prove and verify the proposal.