To generate a medical image with high visibility in fluorescence observation. A medical image generation apparatus (100) according to the present application includes an acquisition unit (131), a calculation unit (132), and a generation unit (134). An acquisition unit (131) acquires a first medical image captured with fluorescence of a predetermined wavelength and a second medical image captured with fluorescence of a wavelength different from the predetermined wavelength. A calculation unit (132) calculates a degree of scattering, indicating a degree of blurring of fluorescence of a living body, included in the first medical image and the second medical image acquired by the acquisition unit (131). A generation unit (134) generates an output image on the basis of at least one of the degrees of scattering calculated by the calculation unit (132).

In a method for processing microscope images, at least one microscope image is provided as input image for an image processing algorithm. An output image is created from the input image by means of the image processing algorithm. The creation of the output image comprises adding low-frequency components for representing solidity of image structures of the input image to the input image, wherein the low-frequency components at least depend on high-frequency components of these image structures and wherein high-frequency components are defined by a higher spatial frequency than low-frequency components. A corresponding computer program and microscope system are likewise described.

An electronic device is provided. The electronic device includes a memory, an image sensor including light receiving elements each including at least two sub light receiving elements, and an image signal processor. The image signal processor is configured to obtain images corresponding to light from outside by using the image sensor, the images including at least a raw image, a first sub image, and a second sub image, the first sub image being an image corresponding to light detected by at least one first sub light, the second sub image being an image corresponding to light detected by at least one second sub light, identify a luminance ratio between the first sub image and the second sub image, identify a defect in the raw image, based on the luminance ratio, and perform a function corresponding to a type of the defect.

Disclosed are an image processing method and apparatus, a computer device and a storage medium, which relate to the field of artificial Intelligence. The method includes receiving an original image; performing image photographing defect detection and color deviation detection on the original image, the image photographing defect detection determining whether there exists a photographing defect that is irreparable through image processing, the color deviation detection determining whether there exists color cast in the original image; performing color correction on the original image if the original image passes the image photographing defect detection and does not pass the color deviation detection; and generating a target image based on the color-corrected original image.

A receiving-side apparatus executes: reception processing for receiving a camera image from a transmitting-side apparatus; determination processing for determining whether execution conditions for performing image quality improvement processing with respect to the camera image are established; in a case where the execution conditions are established, order processing for transmitting the camera image to an external server apparatus connected through a network to the receiving-side apparatus, and ordering the image quality improvement processing with respect to the camera image; processing for receiving an image-quality-improved image generated by performing image quality improvement processing on the camera image from the external server apparatus; and processing for displaying the image-quality-improved image on a display apparatus.

An imaging device 10 according to one aspect of the present invention includes: a subject distance acquisition section 115; a movement amount acquisition section 120 that acquires an amount of movement of the subject on the basis of the subject distance; a restoration processing determination section 125 that determines, on the basis of the amount of movement acquired by the movement amount acquisition section 120, whether the restoration processing should be performed on the images through a restoration filter, a restoration strength of the restoration processing should be adjusted and the restoration processing should be performed on the images, or the restoration processing should not be performed on the images; and a restoration processing execution section 105 that performs the restoration processing on the images through the restoration filter or with the adjusted restoration strength, on the basis of the determination of the restoration processing determination section 125.

An apparatus for measuring a scanning pattern of an optical scanning apparatus can easily reduce the effect of stray light and improve the measurement accuracy of the scanning pattern. An apparatus for measuring a scanning pattern of an optical scanning apparatus (100), which scans an object being illuminated with illumination light and generates a display image of the object being illuminated, includes a screen (11) scanned by the illumination light and an optical position detector (12) that detects the position of an irradiation spot of the illumination light on the screen (11). The apparatus for measuring a scanning pattern sequentially detects a position of the irradiation spot at predetermined time points with the optical position detector (12) during scanning of the screen (11) to measure the scanning pattern of the illumination light.

A computing device may obtain an input image. The input image may have a white point represented by chrominance values that define white color in the input image. Possibly based on colors of the input image, the computing device may generate a two-dimensional chrominance histogram of the input image. The computing device may convolve the two-dimensional chrominance histogram with a filter to create a two-dimensional heat map. Entries in the two-dimensional heat map may represent respective estimates of how close respective tints corresponding to the respective entries are to the white point of the input image. The computing device may select an entry in the two-dimensional heat map that represents a particular value that is within a threshold of a maximum value in the heat map, and based on the selected entry, tint the input image to form an output image.

Implementations of the present disclosure include receiving a training image, providing a hash pattern that is representative of the training image, applying a plurality of filters to the training image to provide a respective plurality of filtered training images, identifying a filter to be associated with the hash pattern based on the plurality of filtered training images, and storing a mapping of the filter to the hash pattern within a set of mapping in a data store.

An apparatus for recognizing an object in an image includes a preprocessing module configured to receive an image including an object and to output a preprocessed image by performing image enhancement processing on the received image to improve a recognition rate of the object included in the received image; and an object recognition module configured to recognize the object included in the image by inputting the preprocessed image to an input layer of an artificial neural network for object recognition.