Author Correction: Non-Invasive Imaging Through Scattering Medium by Using a Reverse Response Wavefront Shaping Technique.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Non-Invasive Imaging Through Scattering Medium by Using a Reverse Response Wavefront Shaping Technique.

Fundamental challenge of imaging through a scattering media has been resolved by various approaches in the past two decades. Optical wavefront shaping technique is one such method in which one shapes the wavefront of light entering a scattering media using a wavefront shaper such that it cancels the scattering effect. It has been the most effective technique in focusing light inside a scattering media. Unfortunately, most of these techniques require direct access to the scattering medium or need to know the scattering properties of the medium beforehand. Through the novel scheme presented on this paper, both the illumination module and the detection are on the same side of the inspected object and the imaging process is a real time fast converging operation. We model the scattering medium being a biological tissue as a matrix having mathematical properties matched to the physical and biological aspects of the sample. In our adaptive optics scheme, we aim to estimate the scattering function and thus to encode the intensity of the illuminating laser light source using DMD (Digital Micromirror Device) with an inverse scattering function of the scattering medium, such that after passing its scattering function a focused beam is obtained. We optimize the pattern to be displayed on the DMD using Particle Swarm Algorithm (PSO) which eventually help in retrieving a 1D object hidden behind the media.

Experimental results of revised Misell algorithm for imaging through weakly scattering biological tissue.

A Static random perturbation weakly scattering media may significantly reduce image quality, in many kinds of applications. An example of such a medium can be a soft tissue such as skin or flesh, through which one may wish to image an object, such as a bone, located behind. In this paper we present experimental results of newly developed deblurring approach for obtaining a better image of objects positioned behind static random perturbation media. This approach for extraction of the high spatial frequencies is based on iterative computation similar to the well-known Gerchberg-Saxton algorithm for phase retrieval. By focusing a camera onto three or more planes positioned between the imaging camera and the perturbation media, we are able to retrieve the phase distribution of those planes and then reconstruct the intensity of the object by numerical free-space propagation of this extracted complex field, to the estimated position of the object.

Superresolved and field-of-view extended digital holography with particle encoding.

We present a new configuration for superresolution (SR) as well as for field-of-view (FOV) extension in a digital holography concept based on random movement of sparse metallic particles. In the SR configuration, the particles are in proximity to the recorded object, while in the FOV configuration, the particles are in proximity to the hologram plane. The particles' movement encodes the high spatial features in the plane of their movement. This high-resolution information can later be decoded by proper numerical postprocessing that either remedies the resolution limitations in the object plane (or the limited NA of the lens) or extends the FOV in the object plane.

Toward fast malaria detection by secondary speckle sensing microscopy.

Diagnosis of malaria must be rapid, accurate, simple to use, portable and low cost, as suggested by the World Health Organization (WHO). Despite recent efforts, the gold standard remains the light microscopy of a stained blood film. This method can detect low parasitemia and identify different species of Plasmodium. However, it is time consuming, it requires well trained microscopist and good instrumentation to minimize misinterpretation, thus the costs are considerable. Moreover, the equipment cannot be easily transported and installed. In this paper we propose a new technique named "secondary speckle sensing microscopy" (S(3)M) based upon extraction of correlation based statistics of speckle patterns generated while illuminating red blood cells with a laser and inspecting them under a microscope. Then, using fuzzy logic ruling and principle component analysis, good quality of separation between healthy and infected red blood cells was demonstrated in preliminary experiments. The proposed technique can be used for automated high rate detection of malaria infected red blood cells.

Optical through-turbulence imaging configuration: experimental validation.

In this Letter the authors present a field experimental validation of an imaging system that, when combined with a special image-processing algorithm, allows obtaining an improved imaging quality through turbulence perturbation. The system includes simultaneous capturing of three differently focused images and performing an iterative Gerchberg-Saxton based processing for phase retrieval. After the phase is retrieved the intensity of the object is reconstructed by numerical free-space propagation of the extracted complex field to the estimated position of the object.

Super-resolution via iterative phase retrieval for blurred and saturated biological images.

One of the most fascinating problems addressed today is retrieving high-resolution data of blurred images obtained from biological objects. In most cases the research relays either on a priory knowledge of the image nature or a large number of images (either of the same object or of different objects obtained by the same imaging setup). If saturation is added to the blurring, most algorithms fail to sharpen the image and in some cases researchers decline to use such images as an input. In this work a single captured blurred and saturated image is given with no a priori knowledge except of the fact that the primary blurring is due to defocused imaging setup. The authors suggest a novel three-stage approach for retrieving higher resolution data from the intensity distribution of the blurred and saturated image. The core of the process is the phase retrieval algorithm suggested by Gerchberg and Saxton in 1972. The new method is explained in details and the algorithm is tested numerically and experimentally on several images to show the improvement in the sharpness of the spatial details.

Fuzzy-logic optical optimization of mainframe CPU and memory.

The allocation of CPU time and memory resources is a familiar problem in organizations with a large number of users and a single mainframe. Usually the amount of resources allocated to a single user is based on the user's own statistics not on the statistics of the entire organization, therefore patterns are not well identified and the allocation system is prodigal. A fuzzy-logic-based algorithm to optimize the CPU and memory distribution among users based on their history is suggested. The algorithm works on heavy and light users separately since they present different patterns to be observed. The result is a set of rules generated by the fuzzy-logic inference engine that will allow the system to use its computing ability in an optimized manner. Test results on data taken from the Faculty of Engineering of Tel Aviv University demonstrate the capabilities of the new algorithm.

Optical generation of fuzzy-based rules.

In the last third of the 20th century, fuzzy logic has risen from a mathematical concept to an applicable approach in soft computing. Today, fuzzy logic is used in control systems for various applications, such as washing machines, train-brake systems, automobile automatic gear, and so forth. The approach of optical implementation of fuzzy inferencing was given by the authors in previous papers, giving an extra emphasis to applications with two dominant inputs. In this paper the authors introduce a real-time optical rule generator for the dual-input fuzzy-inference engine. The paper briefly goes over the dual-input optical implementation of fuzzy-logic inferencing. Then, the concept of constructing a set of rules from given data is discussed. Next, the authors show ways to implement this procedure optically. The discussion is accompanied by an example that illustrates the transformation from raw data into fuzzy set rules.