Abstract: Methodology of unwrapping of phase from an optical image in the presence of both noise and unreliable phase fringes configured to tackle both problems simultaneously and, in the most efficient of multiple related implementations, including at least three prongs: i) SD-ROM based denoising procedure, ii) reliable estimation of the gradient of both the wrapped and unwrapped phase with the use of the forward and inverse Laplacian operators; and iii) fringe quality improvement with the use of Fuzzy Logic based Edge Detection. Transformation of optical images with the use of such methodology to provide an image representing visually-perceivable representation of the object's shape. Computer program product configured to implement the same.

Abstract: Embodiments are disclosed for generating lens blur effects. The disclosed systems and methods comprise receiving a request to apply a lens blur effect to an image, the request identifying an input image and a first disparity map, generating a plurality of disparity maps and a plurality of distance maps based on the first disparity map, splatting influences of pixels of the input image using a plurality of reshaped kernel gradients, gathering aggregations of the splatted influences, and determining a lens blur for a first pixel of the input image in an output image based on the gathered aggregations of the splatted influences.

Abstract: Deception can be evaluated by presenting a set of sentences or words to a testee, including some sentences or words that are expected to evoke significant pupil dilation in a testee who is lying and other sentences or words that are not expected to evoke significant pupil dilation in the testee. Changes in the testee's pupil size are compared to ascertain whether a pupil-dilation response to certain sentences or words is larger than for other sentences or words, and an indication of deceptiveness or non-deceptiveness is output based on the results of the ascertaining.

Abstract: A system for diagnosing a heart condition comprises an imaging system (102) arranged to acquire two images of the heart at respective points in the cardiac cycle, and locating means, which may be manually operated or automatic, for locating a series of pairs of points on the images. Each pair of points indicates the respective positions of a single part of the heart in the two images. The system further comprises a processor (108) arranged to calculate from the positions of said pairs of points a value of at least one parameter of the deformation of the heart. It may further be arranged to compare the value of the at least one parameter with reference data to generate a diagnostic output.

Abstract: Systems, apparatuses, and methods for dynamic filtering of high intensity broadband electromagnetic waves in image data from a sensor of a robot are disclosed herein. According to at least one non-limiting exemplary embodiment, sunlight or light emitted from nearby fluorescent lamps may cause a robot to generate false positives of objects nearby the robot as the light may be of high intensity and large bandwidth. These false positives may cause a robot to get stuck or navigate without use of a camera sensor, which may be unsafe.

Abstract: Processes and techniques are disclosed to identify regions of suspected malignancy and their localization within a body part or organ. These methods rely on the analysis of infrared images to identify thermal abnormalities using image post-processing techniques, numerical modeling, iterative solutions methodology or a digital library. The methods utilize noninvasive, non-radiative and no contact infrared imaging that can be used for breast cancer screening for improved prognosis.

Abstract: Embodiments relate to lateral chromatic aberration (LCA) recovery of raw image data generated by image sensors. A chromatic aberration recovery circuit performs chromatic aberration recovery on the raw image data to correct the resulting LCA in the full color images using pre-calculated offset values of a subset of colors of pixels.

Abstract: In general, intelligent fuel dispensers are provided. In at least some implementations, an intelligent fuel dispenser can determine customer identities and/or other characteristics and provide customized fueling sessions based on the determined customer identities and/or other characteristics. In at least some implementations, the fuel dispenser includes a touchless interface allowing customers to complete fueling sessions with minimal physical contact with the fuel dispenser.

Abstract: A method for estimating baseline in a signal, the signal being represented by input signal data (I(xi)), includes estimating a baseline contribution (I2(xi)) in the signal to obtain baseline estimation data (f(xi)), wherein the baseline estimation data (f(xi)) are computed as a fit to at least a subset of the input signal data (I(xi)) by minimizing a least-square minimization criterion (M(f(xi))). Deblurred output signal data (O(xi)) are obtained based on the baseline estimation data (f(xi)) and the input signal data (I(xi)). The least-square minimization criterion (M(f(xi))) comprises a penalty term (P(f(xi))).

Abstract: An image decoding method according to the present specification comprises the steps of: deriving transform coefficients through inverse quantization on the basis of quantized transform coefficient for a target block; deriving modified transform coefficients on the basis of inverse reduced secondary transform (RST) of the transform coefficients; and generating a reconstructed picture on the basis of residual samples for the target block on the basis of an inverse primary transform of the modified transform coefficients, wherein the step of deriving the modified transform coefficients is characterized in deriving 16 modified transform coefficients by applying a transform kernel matrix to 8 transform coefficients in a 4×4 region of the target block.

Abstract: A polarization imaging unit generates, as polarization information, a polarization image including pixels in a plurality of polarization directions. An interpolation processing unit of an information processor performs interpolation processing using the polarization image obtained from the polarization imaging unit, and generates a polarization image for each polarization method. A polarization degree calculation unit calculates, for example, a polarization degree for each pixel as object surface information on the basis of the polarization image for each polarization method. A noise amount calculation unit calculates a noise amount for each pixel on the basis of the polarization image for each polarization method and the like.

Abstract: The present disclosure relates to systems and methods for image reconstruction. The system may obtain an initial image to be processed. The system may generate a reconstructed image by performing a plurality of iteration steps on the initial image. Each of the plurality of iteration steps may include a first optimization operation and at least one second optimization operation. The first optimization operation and the at least one second optimization operation may be executed sequentially. The first optimization operation may include receiving an image to be processed in the iteration step and determining an updated image by preliminarily optimizing the image to be processed. The at least one second optimization operation may include determining an optimized image by reducing interference information of the updated image and designating the optimized image as a next image to be processed in a next iteration step. The interference information may include noise information and/or artifact information.

Abstract: A generative adversarial network including a generator portion and a discriminator portion is constructed. The network is configured such that the network operates to enhance intensity images, wherein an intensity image is obtained by illuminating an object with an energy pulse and measuring the return strength of the energy pulse, and wherein a pixel of the intensity image corresponds to the return strength. As a part of the configuring, a loss function of the generative adversarial network is minimized, the loss function comprising a mean square error loss measurement of a noisy intensity image relative to a mean square error loss measurement of a corresponding clean intensity image. An enhanced intensity image is generated by applying the minimized loss function of the network to an original intensity image, the applying improving an image quality measurement of the enhanced intensity image relative to the original intensity image.

Abstract: An method and an apparatus for generating an image, and an electronic device are provided. The method comprises: performing a plurality of types of image enhancement processing on an image to be processed respectively to obtain a plurality of pre-enhanced images; performing image quality classification on a first image block in the image to be processed to obtain a first quality classification result for the first image block; determining a target pre-enhanced image from the plurality of pre-enhanced images based on the first quality classification result for the first image block; determining a second image block in the target pre-enhanced image; and generating a target image based on the second image block.

Abstract: A computing system receives, from a client device, image data describing an image captured by an optical sensor of the client device. The computing system compares the image to a set of reference images that include associated metadata describing a real-world feature depicted by the respective reference image. The computing system determines, based on the comparison, a subset of reference images that are similar to the image, and then determines, based on associated metadata of the subset of reference images, that the image captured by the optical sensor of the client device depicts a first real-world feature. The computing system selects a subset of media overlays related to the first real-world feature based on metadata associated with each media overlay that describes the respective media overlay. The computing system transmits the subset of media overlays to the client device.

Abstract: An example apparatus for video imaging includes a feature estimator to calculate a local value of a feature for averaging in a compressed set of features of a current frame. The apparatus also includes a validator to calculate a validity map comprising a weight for frame-wide averaging based on the compressed current frame. The apparatus further includes a vector generator to generate a state vector based on the local value of the feature and the weight. The apparatus further includes a relevance calculator to calculate a relevance to local processing for each coordinate in a restored state vector associated with a previous frame. The apparatus further includes a vector modulator to multiply the restored state vector by the relevance feature to generate a set of output features.

Abstract: Systems and techniques are provided for determining an improved camera coverage plan including a number, a placement, and a pose of cameras that are arranged to track puts and takes of items by subjects in a three-dimensional real space. The method includes receiving an initial camera coverage plan including a three-dimensional map of a real space, an initial number and initial pose of a plurality of cameras and a camera model including characteristics of the cameras. The method can iteratively apply a machine learning process to an objective function of number and poses of cameras, and subject to a set of constraints, obtain an improved camera coverage plan. The improved camera coverage plan is provided to an installer to arrange cameras to track puts and takes of items by subjects in the three-dimensional real space.

Abstract: A system for image quality assessment of non-aligned images includes a first deep path portion of a convolutional neural network having a set of parameters and a second deep path portion of the convolutional neural network sharing a set of parameters with the first deep path convolutional neural network. Weights are shared between the first and second deep path convolutional neural networks to support extraction of a same set of features in each neural network pathway. Non-aligned reference and distorted images are respectively provided to the first and second deep paths of the convolutional neural network for processing. A concatenation layer is connected to both the first and second deep paths convolutional neural network, and a fully connected layer is connected to the concatenation layer to receive input from both the first and second deep paths of the convolutional neural network, generating an image quality assessment as a linear regressor and outputting an image quality score.

Abstract: Apparatuses, systems, and techniques are presented to generate images with one or more visual effects applied. In at least one embodiment, one or more visual effects are applied to one or more images having a resolution that is less than a first resolution and those visual effects approximated for one or more images having a resolution that is greater than or equal to the first resolution.

Abstract: A method of generating a composite image from multiple images captured for a subject is disclosed. In some embodiments, the method may include receiving, via an image capturing device, a plurality of sets of images of at least a portion of a subject. The images within a set of images may be captured at a plurality of vertical positions with respect to an associated fixed section of a horizontal plane. The method may further include generating a plurality of focus-stacked images corresponding to the plurality of sets of images, for example, by combining the images in the associated set of images. The method may further include aligning the plurality of focus-stacked images in the horizontal plane based on a horizontal coordinate transformation model to generate a composite image representing the subject.