A spectral computed tomography imaging system (102) includes a radiation source (112) configured to emit x-ray radiation and a detector array (114) configured to detect x-ray radiation and generate spectral data. The spectral imaging system further includes a memory (134) configured to store a virtual non-contrast image enhancing module (136) that includes computer executable instructions including a neural network trained to produce image quality enhanced virtual non-contrast images. The neural network is trained with training spectral data and training non-contrast-enhanced images generated from a non-contrast-enhanced scan. The spectral imaging system further includes a processor (132) configured to process the spectral data with the trained neural network to produce the image quality enhanced virtual non-contrast images.

A terminal device calibrates a to-be-detected image based on a light source color temperature and scene brightness that are obtained during imaging of the to-be-detected image and based on a preset reference color card image set to restore a real color of the to-be-detected image to a greatest extent.

An electric heater fire extinguishing strategy customization mechanism includes: a timing device for outputting the current operation time; a real-time display device installed onto an integrated circuit board of the electric heater and connected to the timing device for receiving the current operation time and displaying a red string corresponding to the real-time display and too-long operation information of when the current operation time exceeds a limit; a position sensing device installed onto the dot-matrix imaging mechanism for detecting the current position of the dot-matrix imaging mechanism, determining the difference between the current position and a predetermined fixed position, wherein the difference includes a horizontal change and a vertical change, and issuing a jitter sensing signal when the horizontal change changes between positive and negative values or the vertical change changes between positive and negative values. The electric heater includes a fire extinguishing function.

Systems and methods for image modification to increase contrast between text and non-text pixels within the image. In one embodiment, an original document image is scaled to a predetermined size for processing by a convolutional neural network. The convolutional neural network identifies a probability that each pixel in the scaled is text and generates a heat map of these probabilities. The heat map is then scaled back to the size of the original document image, and the probabilities in the heat map are used to adjust the intensities of the text and non-text pixels. For positive text, intensities of text pixels are reduced and intensities of non-text pixels are increased in order to increase the contrast of the text against the background of the image. Optical character recognition may then be performed on the contrast-adjusted image.

A method of predicting optimal values for a plurality of parameters used in an operation of an image signal processor includes: inputting initial values for the plurality of parameters to a machine learning model having an input layer, corresponding to the plurality of parameters, and an output layer corresponding to a plurality of evaluation items extracted from a result image generated by the image signal processor; obtaining evaluation scores for the plurality of evaluation items using an output of the machine learning model; adjusting weights, applied to the plurality of parameters, based on the evaluation scores; and determining the optimal values using the adjusted weights.

The present invention provides a method for image preprocessing, the method including: identifying a plurality of input images to process image registration; selecting at least one transformation method among histogram equalization and gamma transformation in consideration of hue and brightness values of the plurality of input images; processing the histogram equalization on the plurality of input images in response to the histogram equalization method being selected; and processing the gamma transformation on the plurality of input images, in response to the gamma transformation method being selected.

Described are concepts, systems and techniques related to processing an input video signal intended for a first display to produce an output signal appropriate for a second display. The concepts, systems and techniques include converting using one or more transfer functions arranged to provide relative scene light values and remove or apply rendering intent of the input or output video signal, wherein the removing or applying rendering intent alters luminance.

The present invention provides a method and an apparatus for analyzing a cell state, cell death in particular, in an interior of a spheroid non-invasively and quantitatively when the spheroid is cultured. More specifically, the present invention provides a method and an apparatus for analyzing a cell state by implementing optical imaging of a spheroid by using an optical instrument characterized by a high resolution and analyzing the internal structure of the spheroid.

A shadow brightening method includes receiving, at a memory device, an original input image, a brightening level, and a threshold pixel intensity. If a pixel intensity is greater than the threshold, then the pixel is considered bright. Otherwise, the pixel is shadowed. The method includes calculating a gamma transformation for each pixel. If the pixel intensity is less than or equal to the threshold, then a gamma transformation equal to the received brightening level is applied. If the pixel intensity is greater than the threshold, then the gamma transformation is scaled to decrease with intensity. For each shadowed pixel, the method includes computing a minimum value. It also includes determining the brightening level to be applied, thus creating a gamma map. The method also includes applying the determined brightening level to the shadowed pixels and outputting a shadow-brightened output image.

To enable a good HDR image or video coding technology, being able to yield high dynamic range images as well as low dynamic range images, we invented a method of encoding a high dynamic range image (M_HDR), comprising the steps of: converting the high dynamic range image to an image of lower luminance dynamic range (LDR_o) by applying a) scaling the high dynamic range image to a predetermined scale of the luma axis such as [0,1], b) applying a sensitivity tone mapping which changes the brightnesses of pixel colors falling within at least a subrange comprising the darker colors in the high dynamic range image, c) applying a gamma function, and d) applying an arbitrary monotonically increasing function mapping the lumas resulting from performing the steps b and c to output lumas of the lower dynamic range image (LDR_o); and outputting in an image signal (S_im) a codification of the pixel colors of the lower luminance dynamic range image (LDR_o), and outputting in the image signal (S_im) values encoding the functional behavior of the above color conversions as metadata, or values for the inverse functions, which metadata allows to reconstruct a high dynamic range image (Rec_HDR) from the lower luminance dynamic range image (LDR_o).