Theory of coherent active convolved illumination for superresolution enhancement

Recently an optical amplification process called the plasmon injection scheme was introduced as an effective solution to overcoming losses in metamaterials. Implementations with near-field imaging applications have indicated substantial performance enhancements even in the presence of noise. This powerful and versatile compensation technique, which has since been renamed to a more generalized active convolved illumination, offers new possibilities of improving the performance of many previously conceived metamaterial-based devices and conventional imaging systems. In this work, we present the first comprehensive mathematical breakdown of active convolved illumination for coherent imaging. Our analysis highlights the distinctive features of active convolved illumination, such as selective spectral amplification and correlations, and provides a rigorous understanding of the loss compensation process. These features are achieved by an auxiliary source coherently superimposed with the object field. The auxiliary source is designed to have three important properties. First, it is correlated with the object field. Second, it is defined over a finite spectral bandwidth. Third, it is amplified over that selected bandwidth. We derive the variance for the image spectrum and show that utilizing the auxiliary source with the above properties can significantly improve the spectral signal-to-noise ratio and resolution limit. Besides enhanced superresolution imaging, the theory can be potentially generalized to the compensation of information or photon loss in a wide variety of coherent and incoherent linear systems including those, for example, in atmospheric imaging, time-domain spectroscopy, ${\cal PT}$ symmetric non-Hermitian photonics, and even quantum computing.Comment: revised, more details and references adde

Illumination-effects compensation in facial images

Based on the concepts of linear object classes and the principal components analysis, an illumination-effects compensation method is presented to transform an arbitrary-lit face image whose illumination effects are pre-determined, into a front-lit face image

Recursive Copy and Paste GAN: Face Hallucination from Shaded Thumbnails.

Existing face hallucination methods based on convolutional neural networks (CNNs) have achieved impressive performance on low-resolution (LR) faces in a normal illumination condition. However, their performance degrades dramatically when LR faces are captured in non-uniform illumination conditions. This paper proposes a Recursive Copy and Paste Generative Adversarial Network (Re-CPGAN) to recover authentic high-resolution (HR) face images while compensating for non-uniform illumination. To this end, we develop two key components in our Re-CPGAN: internal and recursive external Copy and Paste networks (CPnets). Our internal CPnet exploits facial self-similarity information residing in the input image to enhance facial details; while our recursive external CPnet leverages an external guided face for illumination compensation. Specifically, our recursive external CPnet stacks multiple external Copy and Paste (EX-CP) units in a compact model to learn normal illumination and enhance facial details recursively. By doing so, our method offsets illumination and upsamples facial details progressively in a coarse-to-fine fashion, thus alleviating the ambiguity of correspondences between LR inputs and external guided inputs. Furthermore, a new illumination compensation loss is developed to capture illumination from the external guided face image effectively. Extensive experiments demonstrate that our method achieves authentic HR images in a uniform illumination condition with a 16x magnification factor and outperforms state-of-the-art methods qualitatively and quantitatively

Enhanced nonlinear imaging through scattering media using transmission matrix based wavefront shaping

Despite the tremendous progresses in wavefront control through or inside complex scattering media, several limitations prevent reaching practical feasibility for nonlinear imaging in biological tissues. While the optimization of nonlinear signals might suffer from low signal to noise conditions and from possible artifacts at large penetration depths, it has nevertheless been largely used in the multiple scattering regime since it provides a guide star mechanism as well as an intrinsic compensation for spatiotemporal distortions. Here, we demonstrate the benefit of Transmission Matrix (TM) based approaches under broadband illumination conditions, to perform nonlinear imaging. Using ultrashort pulse illumination with spectral bandwidth comparable but still lower than the spectral width of the scattering medium, we show strong nonlinear enhancements of several orders of magnitude, through thicknesses of a few transport mean free paths, which corresponds to millimeters in biological tissues. Linear TM refocusing is moreover compatible with fast scanning nonlinear imaging and potentially with acoustic based methods, which paves the way for nonlinear microscopy deep inside scattering media

A 14% efficient nonaqueous semiconductor/liquid junction solar cell

We describe the most efficient semiconductor/liquid junction solar cell reported to date. Under W‐halogen (ELH) illumination, the device is a 14% efficient two‐electrode solar cell fabricated from an n‐type silicon photoanode in contact with a nonaqueous electrolyte solution. The cell′s central feature is an ultrathin electrolyte layer which simultaneously reduces losses which result from electrode polarization, electrolyte light absorption, and electrolyte resistance. The thin electrolyte layer also eliminates the need for forced convection of the redox couple and allows for precise control over the amount of water (and other electrolyte impurities) exposed to the semiconductor. After one month of continuous operation under ELH light at 100 mW/cm^2, which corresponds to the passage of over 70 000 C/cm^2, thin‐layer cells retained over 90% of their efficiency. In addition, when made with Wacker Silso cast polycrystalline Si, cells yield an efficiency of 9.8% under simulated AMl illumination. The thin‐layer cells employ no external compensation yet surpass their corresponding experimental (three‐electrode) predecessors in efficiency

The effect of illumination compensation methods with histogram back projection for camshift application

This paper presents the results of a factorial experiment performed to determine the effect ofillumination compensation methods with histogram back projection to be used for objecttracking algorithm continuous adaptive mean-shift (Camshift). Since Camshift tracking can beused for distance approximation of an object, a precise tracker algorithm is required. Thisstudy compared two types of illumination compensation methods using Design of Experiment(DOE) in the presence of illumination inconsistency. Based on the results, it was found thatselecting two channels as reference in histogram back projection weakens the accuracy ofCamshift tracking whereas the combination of both methods produces results that are moredesirable.Keywords: object tracking; camshift; vision system; DOE

Active plasmon injection scheme for subdiffraction imaging with imperfect negative index flat lens

We present an active physical implementation of the recently introduced plasmon injection loss compensation scheme for Pendry's non-ideal negative index flat lens in the presence of realistic material losses and signal-dependent noise. In this active implementation, we propose to use a physically convolved external auxiliary source for signal amplification and suppression of the noise in the imaging system. In comparison with the previous passive implementations of the plasmon injection scheme for sub-diffraction limited imaging, where an inverse filter post-processing is used, the active implementation proposed here allows for deeper subwavelength imaging far beyond the passive post-processing scheme by extending the loss compensation to even higher spatial frequencies.Comment: 13 pages, 15 figure

Intrinsic Image Transfer for Illumination Manipulation

This paper presents a novel intrinsic image transfer (IIT) algorithm for illumination manipulation, which creates a local image translation between two illumination surfaces. This model is built on an optimization-based framework consisting of three photo-realistic losses defined on the sub-layers factorized by an intrinsic image decomposition. We illustrate that all losses can be reduced without the necessity of taking an intrinsic image decomposition under the well-known spatial-varying illumination illumination-invariant reflectance prior knowledge. Moreover, with a series of relaxations, all of them can be directly defined on images, giving a closed-form solution for image illumination manipulation. This new paradigm differs from the prevailing Retinex-based algorithms, as it provides an implicit way to deal with the per-pixel image illumination. We finally demonstrate its versatility and benefits to the illumination-related tasks such as illumination compensation, image enhancement, and high dynamic range (HDR) image compression, and show the high-quality results on natural image datasets

Characterization of modulated time-of-flight range image sensors

A number of full field image sensors have been developed that are capable of simultaneously measuring intensity and distance (range) for every pixel in a given scene using an indirect time-of-flight measurement technique. A light source is intensity modulated at a frequency between 10–100 MHz, and an image sensor is modulated at the same frequency, synchronously sampling light reflected from objects in the scene (homodyne detection). The time of flight is manifested as a phase shift in the illumination modulation envelope, which can be determined from the sampled data simultaneously for each pixel in the scene. This paper presents a method of characterizing the high frequency modulation response of these image sensors, using a pico-second laser pulser. The characterization results allow the optimal operating parameters, such as the modulation frequency, to be identified in order to maximize the range measurement precision for a given sensor. A number of potential sources of error exist when using these sensors, including deficiencies in the modulation waveform shape, duty cycle, or phase, resulting in contamination of the resultant range data. From the characterization data these parameters can be identified and compensated for by modifying the sensor hardware or through post processing of the acquired range measurements