A method for measuring distorted illumination patterns and correcting image artifacts in structured illumination microscopy. The method includes the steps of generating an illumination pattern by interfering multiple beams, modulating a scanning speed or an intensity of a scanning laser, or projecting a mask onto an object; taking multiple exposures of the object with the illumination pattern shifting in phase; and applying Fourier transform to the multiple exposures to produce multiple raw images. Thereafter, the multiple raw images are used to form and then solve a linear equation set to obtain multiple portions of a Fourier space image of the object. A circular 2-D low pass filter and a Fourier Transform are then applied to the portions. A pattern distortion phase map is calculated and then corrected by making a coefficient matrix of the linear equation set varying in phase, which is solved in the spatial domain.

A pattern recognition system including an image gathering unit that gathers at least one digital representation of a field, an image analysis unit that pre-processes the at least one digital representation of a field, an annotation unit that provides a visualization of at least one channel for each of the at least one digital representation of the field, where the image analysis unit generates a plurality of image samples from each of the at least one digital representation of the field, and the image analysis unit splits each of the image samples into a plurality of categories.

This invention provides a signal-processing method that makes it possible to acquire, relatively easily and surely, a highly reliable normalized impulse-response signal without relying on the signal-correction processing after normalization. The signal-processing method of this invention includes a low-frequency extraction step, a high-frequency extraction step and a synthesizing step. In the low-frequency extraction step, only the low-frequency component is extracted from the spectrum of the first normalized signal NS1 obtained by normalizing the target signal S.sub.tgt in the time domain. In the high-frequency extraction step, only the high-frequency component is extracted from the spectrum of the second normalized signal NS2 obtained by normalizing the target signal S.sub.tgt in the frequency domain using the reference signal S.sub.ref. In the synthesizing step, the low-frequency component, derived from the first normalized signal NS1, and the high-frequency component, derived from the second normalized signal NS2, are synthesized to obtain a normalized impulse-response signal NS.

A system can receive downhole acquisition data relating to a wellbore. The system can pre-process the downhole acquisition data. The system can generate an incomplete borehole image using the downhole acquisition data. The system can determine a sparse representation based on the incomplete borehole image by performing an optimization with respect to the incomplete borehole image. The system can generate a complete borehole image based on an inverse of the sparse representation.

There are provided techniques for analyzing an atom probe tomography data set obtained from a tip-shaped sample. The techniques include defining analysis sub-volumes in the atom probe tomography data set; performing a fast Fourier transform (FFT) on each of the analysis sub-volumes to obtain a signal in a Fourier domain; identifying at least one FFT peak in the signal in the Fourier domain, each FFT peak being indicative of an expected crystal feature in the corresponding analysis sub-volume; continuously and automatically calculating an image compression factor and a radius of the tip-shaped sample, based on identified crystal features, the identified crystal features being obtained from a collection of expected crystal features; and reconstructing a three-dimensional model of the tip-shaped sample. Said reconstructing includes comparing the identified crystal features with calibration data; and dynamically adjusting the image compression factor and the radius of the tip-shaped sample.

A method for detecting fake images includes: obtaining an image for authentication, and hand-crafting a multi-attribute classifier to determine whether the image is authentic. Hand-crafting the multi-attribute classifier includes fusing at least an image classifier, an image spectrum classifier, a co-occurrence matrix classifier, and a one-dimensional (1D) power spectrum density (PSD) classifier. The multi-attribute classifier is trained by pre-processing training images to generate an attribute-specific training dataset to train each of the image classifier, the image spectrum classifier, the co-occurrence matrix classifier, and the 1D PSD classifier.

An object information obtaining device includes a light source which emits light, an acoustic wave detecting unit which detects a photoacoustic wave generated by irradiation of an object with the light, and outputs an electric signal in response to detection of the photoacoustic wave, and a processing unit configured to perform two or more types of processing to photoacoustic signal data based on the electric signal to obtain object information corresponding to each of the two or more types of processing, and to display on a display unit the object information corresponding to at least one processing selected by a user out of the two or more types of processing.

The present disclosure is directed toward systems and methods that efficiently and effectively generate an enhanced document image of a displayed document in an image frame captured from a live image feed. For example, systems and methods described herein apply a document enhancement process to a displayed document in an image frame that result in an enhanced document image that is cropped, rectified, un-shadowed, and with dark text against a mostly white background. Additionally, systems and method described herein determine whether a stored digital content item includes a displayed document. In response to determining that a stored digital content item does include a displayed document, systems and methods described herein generate an enhanced document image of a displayed document included in the stored digital content item.

In one embodiment, an apparatus comprises a memory and a processor. The memory is to store visual data associated with a visual representation captured by one or more sensors. The processor is to: obtain the visual data associated with the visual representation captured by the one or more sensors, wherein the visual data comprises uncompressed visual data or compressed visual data; process the visual data using a convolutional neural network (CNN), wherein the CNN comprises a plurality of layers, wherein the plurality of layers comprises a plurality of filters, and wherein the plurality of filters comprises one or more pixel-domain filters to perform processing associated with uncompressed data and one or more compressed-domain filters to perform processing associated with compressed data; and classify the visual data based on an output of the CNN.

A method assess the quality of varnished wood surfaces. The method includes the following steps: a) creating a brightness map of the surface, b) creating a curvature map of the surface, c) ascertaining a cross-correlation of brightness map and curvature map, and d) evaluating the result of the cross-correlation to ascertain the proportion of the irregularities of the surface to be attributed to varnish flaws.