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Consequently, this assists nanoscopy methods such as SOFI to better support super-resolution, which is otherwise compromised due to spatial correlation of the mode patterns in the raw image. Furthermore, applying HAWK prior to SOFI alleviates the problem of artifacts due to non-uniform illumination without degrading temporal resolution. Our experimental results demonstrate resolution enhancement as well as reduction in artifacts through the combination of HAWK and SOFI.Fourier Ptychographic Microscopy (FPM) allows high resolution imaging using iterative phase retrieval to recover an estimate of the complex object from a series of images captured under oblique illumination. FPM is particularly sensitive to noise and uncorrected background signals as it relies on combining information from brightfield and noisy darkfield (DF) images. In this article we consider the impact of different noise sources in FPM and show that inadequate removal of the DF background signal and associated noise are the predominant cause of artefacts in reconstructed images. We propose a simple solution to FPM background correction and denoising that outperforms existing methods in terms of image quality, speed and simplicity, whilst maintaining high spatial resolution and sharpness of the reconstructed image. Our method takes advantage of the data redundancy in real space within the acquired dataset to boost the signal-to-background ratio in the captured DF images, before optimally suppressing background signal. By incorporating differentially denoised images within the classic FPM iterative phase retrieval algorithm, we show that it is possible to achieve efficient removal of background artefacts without suppression of high frequency information. The method is tested using simulated data and experimental images of thin blood films, bone marrow and liver tissue sections. Our approach is non-parametric, requires no prior knowledge of the noise distribution and can be directly applied to other hardware platforms and reconstruction algorithms making it widely applicable in FPM.Optical interrogation of tissues is broadly considered in biomedical applications. Nevertheless, light scattering by tissue limits the resolution and accuracy achieved when investigating sub-surface tissue features. Light carrying optical angular momentum or complex polarization profiles, offers different propagation characteristics through scattering media compared to light with unstructured beam profiles. Here we discuss the behaviour of structured light scattered by tissue-mimicking phantoms. We study the spatial and the polarization profile of the scattered modes as a function of a range of optical parameters of the phantoms, with varying scattering and absorption coefficients and of different lengths. These results show the non-trivial trade-off between the advantages of structured light profiles and mode broadening, stimulating further investigations in this direction.With the development of optical information processing technology, image edge enhancement technology has rapidly received extensive attention, especially in the field of quantum imaging. find more However, quantum edge enhanced imaging faces challenges in terms of time-consuming acquisition processes and the complexity of the devices used, which limits practical applications in real-time usage scenarios. Here we introduce and experimentally demonstrate a real-time (0.5 Hz) quantum edge enhanced imaging method that combines the spiral phase contrast technique with heralded single-photon imaging. The edge enhancement results show high quality and background free from raw data. Compared with direct imaging, our configuration can improve the signal-to-noise ratio significantly using the tight time correlations between photon pairs. The method also offers competitive advantages over ghost imaging, including higher brightness and a compact optical fiber delay rather than a free space delay. Additionally, we explore curved edge enhancement for specific feature recognition and the oriented shadow effect. Overall, this efficient and versatile platform paves an alternative path toward real-time quantum edge detection in applications including nondestructive bio-imaging, night vision and covert monitoring.A strategically constructed substrate, patterned sapphire with silica array (PSSA), was developed to boost the efficiency of patterned sapphire substrate (PSS) in GaN-based light-emitting diodes (LEDs) application. The light output power of a flip-chip LED on PSSA improved by 16.5% at 120 mA than that of device grown on PSS. The XRD and STEM measurements revealed that the GaN epilayer grown on PSSA had better crystalline quality compared to the epilayer grown on PSS, which was the result of decreased misfit at coalescence boundary in the PSSA case. Moreover, the light extraction efficiency of the flip-chip LED on PSSA was significantly enhanced, benefiting from the small refractive-index contrast between the patterned silica array and air. This small refractive-index contrast also contributed to a more convergent emission pattern for the flip-chip LED on PSSA, as demonstrated by the far-field radiation pattern measurements. The discovery that PSSA could excel at defect suppression and light extraction revealed a new substrate platform for III-nitride optoelectronic devices.Division of focal plane (DoFP), or integrated microgrid polarimeters, typically consist of a 2 × 2 mosaic of linear polarization filters overlaid upon a focal plane array sensor and obtain temporally synchronized polarized intensity measurements across a scene, similar in concept to a Bayer color filter array camera. However, the resulting estimated polarimetric images suffer a loss in resolution and can be plagued by aliasing due to the spatially-modulated microgrid measurement strategy. Demosaicing strategies have been proposed that attempt to minimize these effects, but result in some level of residual artifacts. In this work we propose a conditional generative adversarial network (cGAN) approach to the microgrid demosaicing problem. We evaluate the performance of our approach against full-resolution division-of-time polarimeter data as well as compare against both traditional and recent microgrid demosaicing methods. We apply these demosaicing strategies to data from both real and simulated visible microgrid imagery and provide an objective criteria for evaluating their performance.