Anisoplanatic deconvolution of adaptive optics images

Spinning pupil aberration measurement for anisoplanatic deconvolution

The aberrations in an optical microscope are commonly measured and corrected at one location in the field of view, within the so-called isoplanatic patch. Full-field correction is desirable for high-resolution imaging of large specimens. Here we present, to the best of our knowledge, a novel wavefront detector, based on pupil sampling with subapertures, measuring the aberrated wavefront phase at each position of the specimen. Based on this measurement, we propose a region-wise deconvolution that provides an anisoplanatic reconstruction of the sample image. Our results indicate that the measurement and correction of the aberrations can be performed in a wide-field fluorescence microscope over its entire field of view.

Miniscope3D: optimized single-shot miniature 3D fluorescence microscopy

Miniature fluorescence microscopes are a standard tool in systems biology. However, widefield miniature microscopes capture only 2D information, and modifications that enable 3D capabilities increase the size and weight and have poor resolution outside a narrow depth range. Here, we achieve the 3D capability by replacing the tube lens of a conventional 2D Miniscope with an optimized multifocal phase mask at the objective's aperture stop. Placing the phase mask at the aperture stop significantly reduces the size of the device, and varying the focal lengths enables a uniform resolution across a wide depth range. The phase mask encodes the 3D fluorescence intensity into a single 2D measurement, and the 3D volume is recovered by solving a sparsity-constrained inverse problem. We provide methods for designing and fabricating the phase mask and an efficient forward model that accounts for the field-varying aberrations in miniature objectives. We demonstrate a prototype that is 17 mm tall and weighs 2.5 grams, achieving 2.76 μm lateral, and 15 μm axial resolution across most of the 900 × 700 × 390 μm3 volume at 40 volumes per second. The performance is validated experimentally on resolution targets, dynamic biological samples, and mouse brain tissue. Compared with existing miniature single-shot volume-capture implementations, our system is smaller and lighter and achieves a more than 2× better lateral and axial resolution throughout a 10× larger usable depth range. Our microscope design provides single-shot 3D imaging for applications where a compact platform matters, such as volumetric neural imaging in freely moving animals and 3D motion studies of dynamic samples in incubators and lab-on-a-chip devices.

Deconvolution for multimode fiber imaging: modeling of spatially variant PSF

Focusing light through a step-index multimode optical fiber (MMF) using wavefront control enables minimally-invasive endoscopy of biological tissue. The point spread function (PSF) of such an imaging system is spatially variant, and this variation limits compensation for blurring using most deconvolution algorithms as they require a uniform PSF. However, modeling the spatially variant PSF into a series of spatially invariant PSFs re-opens the possibility of deconvolution. To achieve this we developed svmPSF: an open-source Java-based framework compatible with ImageJ. The approach takes a series of point response measurements across the field-of-view (FOV) and applies principal component analysis to the measurements' co-variance matrix to generate a PSF model. By combining the svmPSF output with a modified Richardson-Lucy deconvolution algorithm, we were able to deblur and regularize fluorescence images of beads and live neurons acquired with a MMF, and thus effectively increasing the FOV.

Locally adaptive super-resolution through spatially variant interpolation

Systems that do not meet the requirements of the sampling theorem produce images corrupted by aliasing. Higher resolution images are attainable by unfolding aliased spatial frequencies. Multiple-image super-resolution has seen much attention in the literature though with no clear optimum algorithm for many real-world applications. We propose a method of multiframe super-resolution using a set of convolutional sinc kernels, tailored to the specific shifts between images, capable of resolving up to the diffraction limit. We demonstrate our method for the case of global shifts before we treat a pixel-level super-resolution.

Fast image restoration for spatially varying defocus blur of imaging sensor

This paper presents a fast adaptive image restoration method for removing spatially varying out-of-focus blur of a general imaging sensor. After estimating the parameters of space-variant point-spread-function (PSF) using the derivative in each uniformly blurred region, the proposed method performs spatially adaptive image restoration by selecting the optimal restoration filter according to the estimated blur parameters. Each restoration filter is implemented in the form of a combination of multiple FIR filters, which guarantees the fast image restoration without the need of iterative or recursive processing. Experimental results show that the proposed method outperforms existing space-invariant restoration methods in the sense of both objective and subjective performance measures. The proposed algorithm can be employed to a wide area of image restoration applications, such as mobile imaging devices, robot vision, and satellite image processing.

High-resolution retinal imaging with micro adaptive optics system

Based on the dynamic characteristics of human eye aberration, a microadaptive optics retina imaging system set is established for real-time wavefront measurement and correction. This paper analyzes the working principles of a 127-unit Hartmann-Shack wavefront sensor and a 37-channel micromachine membrane deformable mirror adopted in the system. The proposed system achieves wavefront reconstruction through the adaptive centroid detection method and the mode reconstruction algorithm of Zernike polynomials, so that human eye aberration can be measured accurately. Meanwhile, according to the adaptive optics aberration correction control model, a closed-loop iterative aberration correction algorithm based on Smith control is presented to realize efficient and real-time correction of human eye aberration with different characteristics, and characteristics of the time domain of the system are also optimized. According to the experiment results tested on a USAF 1951 standard resolution target and a living human retina (subject ZHY), the resolution of the system can reach 3.6 LP/mm, and the human eye wavefront aberration of 0.728λ (λ=785 nm) can be corrected to 0.081λ in root mean square (RMS) so as to achieve the diffraction limit (Strehl ratio is 0.866), then high-resolution retina images are obtained.

Satellite image restoration in the context of a spatially varying point spread function

In this paper, we consider a deconvolution problem where the point spread function (PSF) of the optical imaging system varies between different spatial locations, thus leading to a spatially varying blur. This problem arises, for example, in synthetic aperture instruments and in wide-field optical systems. Unlike the classical deconvolution context where the PSF is assumed to be spatially invariant, the problem cannot be easily solved in the Fourier domain. We propose here an iterative algorithm based on convex optimization techniques and a wavelet frame regularization. This approach allows restoration of the image, taking into account the properties of the blur operator, the latter being known.