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.

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 visual inspection device and apparatus is disclosed for inspecting fiber ends of a connector by capturing an image of the connector end face, and implementing an image analysis tool for detecting contamination from the captured image. The visual inspection tool includes components for providing a larger field of view to capture the entire connector end face in a single image, and the image analysis tool is able to accurately and efficiently detect contamination from the captured image.

Computer-implemented image correction for a biomarker test includes a biomarker test which has a calibration array and a biomarker site, wherein the calibration array comprises plural colored patches and the biomarker site is color-responsive to indicate a measurement of biomarkers present. The method comprises: storing a reference color value for each of the plural colored patches; receiving an image of the biomarker test; defining shading of pixels of the image as D, a combination of a plurality of basis functions; defining a color correction matrix, M having parameters that when solved correct color of the calibration array in the image to the corresponding stored values; solving D and M for pixels of the image excluding pixels of the biomarker site; using D and M to interpolate values for pixels of the biomarker site of the image to generate a color and shading corrected image of the biomarker site.

An image processing method includes converting an original image represented by a first color space into the original image represented by a second color space, where a correlation between color components of respective channels in the second color space of the original image is smaller than a correlation between color components of respective channels in the first color space; denoising channel images formed by the color components of the respective channels in the second color space respectively to obtain denoised images corresponding to the respective channel images; and obtaining a target image based on the denoised images.

A method, apparatus, and a non-transitory computer-readable storage medium for sub-band image reconstruction. The method may include obtaining an image captured by a camera. The method may also obtain a transform image based on the image captured by the camera. The transform image may be in a transform domain. The method may further obtain decomposed image components of the transform image. The decomposed image components may include a low frequency component and at least one high frequency component. The method may also obtain a reconstructed image based on at least two neural networks processing the decomposed image components in the transform domain

A method and/or device for predicting a compression quality of an image during image correction (e.g., image quality enhancement) in an electronic device, and/or processing the image, based on at least the prediction, may be provided. The electronic device may include a display module, a memory, and a processor, wherein the processor may operate to display an image through the display module, extract designated multiple blocks from the image in a designated scheme, estimate confidence for each of the multiple blocks, identify, based on the estimation of the confidence, a first block corresponding to an outlier to be excluded in quality prediction, and a second block for which quality prediction is possible, among the multiple blocks, exclude the first block among the multiple blocks from a subject of quality prediction, and classify a compression quality of the image by using at least the second block remaining after excluding the first block from among the multiple blocks.

Methods and systems for angiographic imaging with optical coherence tomography (OCT) are described using ratio-based and angiographic deviation based calculations. In using these calculations to determine motion, arbitrary interframe permutations may be used, post- calculated, non-linear results for projection visualization may be averaged, poor matches may be eliminated on an A-line by A-line basis, windowing functions may be used to improve results, partial spectrums may be used when capturing data, and a minimum intensity threshold may be used for determining which pixels to use.

An image processing system includes: a material image generating circuit, at least one texture generating circuit and an output controller. The material image generating circuit is configured to generate a material image. The at least one texture generating circuit is coupled to the material image generating circuit, and configured to adjust texture characteristics of the material image to generate at least one texture image. The output controller is coupled to the at least one texture generating circuit, and configured to analyze regional characteristics of a source image to generate an analysis result, determine a region weight according to the analysis result, and synthesize the source image with the at least one texture image according to the region weight, thereby to generate an output image.

Methods and apparatus are disclosed for producing high quality images in uncontrolled or impaired environments. In some examples of the disclosed technology, groups of cameras for high dynamic range (HDR), polarization diversity, and optional other diversity modes are arranged to concurrently image a common scene. For example, in a vehicle checkpoint application, HDR provides discernment of dark objects inside a vehicle, while polarization diversity aids in rejecting glare. Spectral diversity, infrared imaging, and active illumination can be applied for better imaging through a windshield. Preprocessed single-camera images are registered and fused. Faces or other features of interest can be detected in the fused image and identified in a library. Impairments can include weather, insufficient or interfering lighting, shadows, reflections, window glass, occlusions, or moving objects.