Experimental demonstration of scene-based cophasing in optical synthetic aperture imaging using the SPGD algorithm.

Large-aperture telescopes based on optical synthetic aperture imaging are investigated for recent high-resolution spaceborne observations. An enabling technique of aperture synthesis is a cophasing method to suppress a piston-tip-tilt error between sub-apertures. This paper proposes a scene-based cophasing technique using the stochastic parallel gradient descent (SPGD) algorithm, assuming application to high-resolution Earth observation.

Sequential phase diversity for wavefront correction using a deformable mirror with modeling errors.

The phase diversity (PD) method is effective for scene-based wavefront sensing and control (WFSC) in spaceborne high-resolution imagers for Earth observation. The simplest way of performing the PD WFSC is offering a diversity wavefront by directly actuating a corrective device, such as a deformable mirror. However, this strategy faces a challenge in constructing a numerical model of the provided diversity wavefront because some corrective actuators' properties prevent us from precisely determining their deflection behaviors.

Sequential phase diversity for wavefront correction using a deformable mirror with modeling errors: publisher's note.

This publisher's note corrects an error in Appl. Opt.62, 7931 (2023)APOPAI0003-693510.

Deviation-based wavefront correction using the SPGD algorithm for high-resolution optical remote sensing.

Model-free image-based wavefront correction techniques, such as the stochastic parallel gradient descent (SPGD) algorithm, will be useful in achieving diffraction-limited optical performance in near-future optical remote sensing systems. One difficulty facing the image-based method is that the correction performance depends on the evaluation metric and the evaluated scene. We propose several evaluation functions and investigate the relationship between the optimization speed and the scene textures for each metric in the SPGD algorithm.

Detection and correction of spectral and spatial misregistrations for hyperspectral data using phase correlation method.

Hyperspectral imaging sensors suffer from spectral and spatial misregistrations due to optical-system aberrations and misalignments. These artifacts distort spectral signatures that are specific to target objects and thus reduce classification accuracy. The main objective of this work is to detect and correct spectral and spatial misregistrations of hyperspectral images.