Abstract:
Disclosed are an image processing method and device, a training method of a neural network and a storage medium. The image processing method includes: obtaining an input image, and processing the input image by using a generative network to generate an output image. The generative network includes a first sub-network and at least one second sub-network, and the processing the input image by using the generative network to generate the output image includes, processing the input image by using the first sub-network to obtain a plurality of first feature images; performing a branching process and a weight sharing process on the plurality of first feature images by using the at least one second sub-network to obtain a plurality of second feature images; and processing the plurality of second feature images to obtain the output image.
Abstract:
The present disclosure provides a color compensation circuit, a display apparatus, and a color compensation method, wherein the color compensation circuit comprises an acquisition unit for acquiring, from a video signal, gray image of a frame to be displayed and chrominance image of any color; wherein a chrominance value in the video signal, corresponding to at least a portion of pixels within the chrominance image, is absent; a processing unit for smoothly processing the chrominance value in the chrominance image according to the change trend of gray value in the gray image to obtain a chrominance image with color compensated. The present disclosure can solve the problem that compression and decompression of a video signal during transmission will significantly decrease the frame display effect, and thereby helping improve the frame display effect in a transmission scenario with the loss of chrominance value of the video signal.
Abstract:
There is provided a video signal transmission apparatus, a play system and a transmission method. The video signal transmission apparatus comprises: a first interface configured to be connected with a video signal source; a second interface configured to be connected with a display device; a signal receiving unit and a control unit arranged between the first interface and the second interface, the control unit being connected with the display device through the second interface and the signal receiving unit being connected with the video signal source through the first interface. The control unit comprises an acquiring module configured to acquire parameter information of the display device and feed acquired parameter information back to the signal receiving unit., the parameter information comprising a video format supported by the display device; the signal receiving unit comprises a converting module configured to convert a received video signal into the video format supported by the display device according to the parameter information. The present disclosure can realize plugging and playing and avoid such problem that the system has a failure of output or disorder of display configuration caused by the hot swap or disconnection with the display device and thus needs to be restarted, and so on.
Abstract:
The present disclosure provides an image processing method, an image processing device, and a display device. The image processing method includes: acquiring image data including display data of all of pixels of an image; and performing, on the display data of each of the pixels, operations of: determining Euclidean distances from the display data of the pixel to the display data of a first pure color, the display data of a second pure color, and the display data of a third pure color in a set color space; and replacing the display data of the pixel with one of the display data of the first pure color, the display data of the second pure color and the display data of the third pure color according to the determined Euclidean distances and a preset rule.
Abstract:
There is provided an image representation method, including: converting a to-be-converted image from a first color space to a second color space; acquiring a target conversion color ratio corresponding to each pixel of the to-be-converted image and including ratios of plural target conversion colors, according to a color ratio allocation table based on the second color space; creating an array corresponding to the pixel according to the target conversion color ratio; calculating an index value corresponding to the pixel according to a position of the pixel in the to-be-converted image, and inputting the index value to the array as a subscript of the array, to acquire an element of the array as a target value corresponding to the pixel; and determining a target conversion color of the pixel according to the target value, to acquire a converted image including the plural target conversion colors.
Abstract:
Disclosed is a two-dimensional code image generation method and apparatus, a storage medium and an electronic device related to the field of two-dimensional code image technology. The method includes obtaining an initial two-dimensional code image and a background image, and performing structured processing on the initial two-dimensional code image according to the background image to obtain a structured two-dimensional code image, performing mode transfer processing on the background image to obtain a background image of a target mode by a mode transfer model, and performing a fusion operation on the structured two-dimensional code image and the background image of the target mode to obtain a target two-dimensional code image.
Abstract:
Proposed is a human face resolution re-establishing method based on machine learning, which retains overall structure information about a human face in the process of realizing image resolution improvement, and avoids the occurrence of a local distortion in a generated output image. The human face resolution re-establishing method includes: acquiring an input image, the input image having a first resolution; based on the input image and a standard gradient image library having a second resolution, determining image gradient information about the input image; fusing the image gradient information, and superposing the gradient information obtained through fusion onto the input image; and generating an output image, the output image having a third resolution, wherein the second resolution and the third resolution are both greater than the first resolution.
Abstract:
A display system is disclosed. Light emitting diodes and laser diodes are used to provide backlight sources for the display panel. A first driving unit configured for driving light emitting diodes to emit light and a second driving unit configured for driving laser diodes to emit light are provided accordingly. A control module acquires image signals to be displayed in the display panel and determines whether the image to be displayed need to be compensated for its picture quality; if so, the control module controls a first driving unit and a second driving unit to drive light emitting diodes and laser diodes respectively to emit light together; and if not, only controls a first driving unit to drive light emitting diodes to emit light. The display system can effectively increase color gamut range of a liquid crystal display.
Abstract:
An image processing method and device, and a computer-readable storage medium are disclosed. The method includes: performing a channel expansion process on the input image to obtain a first intermediate image; performing a channel decomposition process for multiple times based on the first intermediate image, wherein each time of channel decomposition process includes: decomposing an image to be processed into a first decomposition image and a second decomposition image; concatenating first decomposition images generated in each time of channel decomposition process and second decomposition image generated in the last time of channel decomposition process to obtain a concatenated image; performing a post-processing process on the concatenated image to obtain a second intermediate image; and fusing the second intermediate image with the input image to obtain the first output image.
Abstract:
A method for processing an image is provided, including: acquiring an input image; performing down-sampling and feature extraction on the input image by an encoder network to obtain multiple feature maps; and performing up-sampling and feature extraction on the multiple feature maps by a decoder network to obtain a target segmentation image; processing levels between the encoder network and the decoder network for outputting feature maps with the same resolution are connected with each other, and the encoder network and the decoder network each includes one or more dense calculation blocks, and at least one convolution module in any dense computation block includes at least one group of asymmetric convolution kernels.