Acquisition and analysis of adaptive optics imaging polarimetry data

The process of data taking, reduction and calibration of near-infrared imaging polarimetry data taken with the ESO Adaptive Optics System ADONIS is described. The ADONIS polarimetric facility is provided by a rotating wire grid polarizer. Images were taken at increments of 22.5 degrees of polarizer rotation from 0 to 180 degrees, over-sampling the polarization curve but allowing the effects of photometric variations to be assessed. Several strategies to remove the detector signature are described. The instrumental polarization was determined, by observations of stars of negligible polarization, to be 1.7% at J, H and K bands. The lack of availability of unpolarized standard stars in the IR, in particular which are not too bright as to saturate current IR detectors, is highlighted. The process of making polarization maps is described. Experiments at restoring polarimetry data, in order to reach diffraction limited polarization, are outlined, with particular reference to data on the Homunculus reflection nebula around Eta Carinae.Comment: 20 pages, A&A LaTeX2e, 11 figures. To appear in Astronomy & Astrophysics, Supplement Serie

Convolutional Deblurring for Natural Imaging

In this paper, we propose a novel design of image deblurring in the form of one-shot convolution filtering that can directly convolve with naturally blurred images for restoration. The problem of optical blurring is a common disadvantage to many imaging applications that suffer from optical imperfections. Despite numerous deconvolution methods that blindly estimate blurring in either inclusive or exclusive forms, they are practically challenging due to high computational cost and low image reconstruction quality. Both conditions of high accuracy and high speed are prerequisites for high-throughput imaging platforms in digital archiving. In such platforms, deblurring is required after image acquisition before being stored, previewed, or processed for high-level interpretation. Therefore, on-the-fly correction of such images is important to avoid possible time delays, mitigate computational expenses, and increase image perception quality. We bridge this gap by synthesizing a deconvolution kernel as a linear combination of Finite Impulse Response (FIR) even-derivative filters that can be directly convolved with blurry input images to boost the frequency fall-off of the Point Spread Function (PSF) associated with the optical blur. We employ a Gaussian low-pass filter to decouple the image denoising problem for image edge deblurring. Furthermore, we propose a blind approach to estimate the PSF statistics for two Gaussian and Laplacian models that are common in many imaging pipelines. Thorough experiments are designed to test and validate the efficiency of the proposed method using 2054 naturally blurred images across six imaging applications and seven state-of-the-art deconvolution methods.Comment: 15 pages, for publication in IEEE Transaction Image Processin

Recent Progress in Image Deblurring

This paper comprehensively reviews the recent development of image deblurring, including non-blind/blind, spatially invariant/variant deblurring techniques. Indeed, these techniques share the same objective of inferring a latent sharp image from one or several corresponding blurry images, while the blind deblurring techniques are also required to derive an accurate blur kernel. Considering the critical role of image restoration in modern imaging systems to provide high-quality images under complex environments such as motion, undesirable lighting conditions, and imperfect system components, image deblurring has attracted growing attention in recent years. From the viewpoint of how to handle the ill-posedness which is a crucial issue in deblurring tasks, existing methods can be grouped into five categories: Bayesian inference framework, variational methods, sparse representation-based methods, homography-based modeling, and region-based methods. In spite of achieving a certain level of development, image deblurring, especially the blind case, is limited in its success by complex application conditions which make the blur kernel hard to obtain and be spatially variant. We provide a holistic understanding and deep insight into image deblurring in this review. An analysis of the empirical evidence for representative methods, practical issues, as well as a discussion of promising future directions are also presented.Comment: 53 pages, 17 figure

In vivo imaging reveals transient microglia recruitment and functional recovery of photoreceptor signaling after injury.

Microglia respond to damage and microenvironmental changes within the central nervous system by morphologically transforming and migrating to the lesion, but the real-time behavior of populations of these resident immune cells and the neurons they support have seldom been observed simultaneously. Here, we have used in vivo high-resolution optical coherence tomography (OCT) and scanning laser ophthalmoscopy with and without adaptive optics to quantify the 3D distribution and dynamics of microglia in the living retina before and after local damage to photoreceptors. Following photoreceptor injury, microglia migrated both laterally and vertically through the retina over many hours, forming a tight cluster within the area of visible damage that resolved over 2 wk. In vivo OCT optophysiological assessment revealed that the photoreceptors occupying the damaged region lost all light-driven signaling during the period of microglia recruitment. Remarkably, photoreceptors recovered function to near-baseline levels after the microglia had departed the injury locus. These results demonstrate the spatiotemporal dynamics of microglia engagement and restoration of neuronal function during tissue remodeling and highlight the need for mechanistic studies that consider the temporal and structural dynamics of neuron-microglia interactions in vivo

Stokes imaging polarimetry using image restoration at the Swedish 1-m Solar Telescope

Aims: We aim to achieve high spatial resolution as well as high polarimetric sensitivity, using an earth-based 1m-class solar telescope, for the study of magnetic fine structure on the Sun. Methods: We use a setup with 3 high-speed, low-noise cameras to construct datasets with interleaved polarimetric states, particularly suitable for Multi-Object Multi-Frame Blind Deconvolution image restorations. We discuss the polarimetric calibration routine as well as various potential sources of error in the results. Results: We obtained near diffraction limited images, with a noise level of approximately 10^(-3) I(cont). We confirm that dark-cores have a weaker magnetic field and at a lower inclination angle with respect to the solar surface than the edges of the penumbral filament. We show that the magnetic field strength in faculae-striations is significantly lower than in other nearby parts of the faculae.Comment: Accepted for publication in Astronomy & Astrophysics, 12 pages, 11 figure

Advanced technology development for image gathering, coding, and processing

Three overlapping areas of research activities are presented: (1) Information theory and optimal filtering are extended to visual information acquisition and processing. The goal is to provide a comprehensive methodology for quantitatively assessing the end-to-end performance of image gathering, coding, and processing. (2) Focal-plane processing techniques and technology are developed to combine effectively image gathering with coding. The emphasis is on low-level vision processing akin to the retinal processing in human vision. (3) A breadboard adaptive image-coding system is being assembled. This system will be used to develop and evaluate a number of advanced image-coding technologies and techniques as well as research the concept of adaptive image coding