Example video processing systems and methods are described. In one implementation, compressed video data is received from a recording device. Additionally, metadata associated with the compressed video data is received such that the metadata includes frame-specific metadata associated with frames in the compressed video data. Further, an application program is received and configured to generate a real-time interactive experience for a user based on the compressed video data and the metadata associated with the compressed video data. A non-fungible token (NFT) is generated that includes the compressed video data, the metadata associated with the compressed video data, and the application program.

This application provides a high dynamic range HDR video processing method, an encoding device, and a decoding device. The method includes: obtaining dynamic metadata of an N.sup.th HDR video frame according to a dynamic metadata generation algorithm; calculating a tone-mapping (tone-mapping) curve parameter of the N.sup.th HDR video frame based on the dynamic metadata of the N.sup.th HDR video frame; generating a tone-mapping curve based on the curve parameter; determining, according to a quality assessment algorithm, distortion D′ caused by the tone-mapping curve; comparing D′ and D.sub.T, to determine a mode used by the N.sup.th HDR video frame, where the mode is an automatic mode or a director mode, and D.sub.T is a threshold value; and determining metadata of the N.sup.th HDR video frame based on the determined mode used by the N.sup.th HDR video frame.

The invention relates to the field of computer engineering for processing images that provides increased accuracy of finding and classifying a similar object . The technical result is achieved by: downloading files of a radiographic image which comprise metadata including information about the object or subject of the image and information about the image itself; encrypting the downloaded files if the above-mentioned files comprise personal data about a person; decrypting the above-mentioned, encrypted, downloaded files; and processing the radiographic image, wherein, as a result of the processing, the following occurs: finding and capturing a relevant region of the radiographic image; removing noise from the captured, relevant region of the radiographic image, wherein a region with a found object is meant by a relevant region of the radiographic image; compressing or unzipping a previously processed radiographic image; and finding a similar object in two previously processed images, and processing said object.

The invention concerns a method for converting an input image comprising an input luminance component made of elements into an output image comprising an output luminance component made of elements, the respective ranges of the output luminance component values and input luminance component element values being of different range extension. the method comprises for the input image: computing a value of a general variable representative of at least two input luminance component element values; transforming each input luminance component element value into a corresponding output luminance component element value according to the computed general variable value; and converting the input image using the determined output luminance component element values. The transforming step uses a set of pre-determined output values organized into a 2D Look-Up-Table (2D LUT) comprising two input arrays indexing a set of chosen input luminance component values and a set of chosen general variable values respectively, each pre-determined output value matching a pair of values made of an indexed input luminance component value and an indexed general variable value, the input luminance component element value being transformed into the output luminance component element value using at least one predetermined output value.

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).

A video display device includes performs a first Retinex process on an inputted video and a second Retinex process, which is different from the first Retinex process, on the inputted video. A video composing unit is configured to compose a video processed by the first Retinex processing unit and a video processed by the second Retinex processing unit in accordance with a feature of the inputted video, which is then displayed. In a process of composing the video processed by the first and second Retinex processing units, the video composing unit is configured to perform a process of converting a luminance level for each pixel so that more output luminance levels are assigned to a luminance band having a large frequency distribution to improve visibility of the video. A gain of the luminance level converting process is varied in accordance with an average pixel value level of the inputted video.

Method for compressing a sequence of images comprising a first image and a second image, the method comprising the steps of: generating a first descriptor comprising parameters for displaying a computer-generated graphical element in the first image, the graphical element being of non-photographic origin, and the display parameters not comprising pixel values; processing the second image so as to determine an event which gave rise to a potential variation in the parameters for displaying the graphical element between the first image and the second image; generating a second descriptor comprising an event code indicating the determined event.

A method and apparatus for processing an image signal, an electronic device, and a computer-readable storage medium. The method includes: obtaining a digital image signal of a target image, the target image including object imaging corresponding to an object, identifying a first area of the object imaging in the target image from the digital image signal, removing the object imaging from the target image based on the first area, to obtain a background image corresponding to an original background, performing image inpainting processing on the first area of the background image to obtain a filled image, the filled image including the original background and a perspective background connected to the original background, identifying a second area in the object imaging, and removing an imaging portion corresponding to the second area from the object imaging, and superimposing the obtained adjusted object imaging on the first area.

A computer can operated, including detecting defects, or other physical features, of artificial objects. Image data is received of one or more artificial objects, and applying an image segmentation process to the image data to detect predetermined defects of the one or more artificial objects. The image segmentation process identifies one or more regions of the image data determined to have a likelihood of showing one or more of the predetermined defects. The identified one or more regions is output. The image segmentation process determines severity metrics for the defects in the one or more regions, wherein a severity metric represents a severity or significance of a defect. The image segmentation process further determines a confidence factor for each region of the one or more regions, wherein the confidence factor represents a likelihood of the presence of a predetermined defect in the region.

A method comprising: providing a 3D representation of at least one object as an input for an encoder (500); projecting the 3D representation onto at least one 2D patch (502); generating at least a geometry image and a texture image from the 2D patch (504); generating, based on the geometry image, a mesh comprising a number of vertices (506); mapping the number of vertices to two- dimensional (2D) coordinates of the texture image (508); and signalling said 2D coordinates of the texture image to be applied to the number of vertices of the mesh in or along a bitstream (510).