Abstract: An image display method and device are provided. The method is applied to an electronic device having a display screen and a camera. The method includes: detecting a first operation of turning on the camera by a user; displaying a photographing interface on the display screen in response to the first operation, where the photographing interface includes a viewfinder frame including a first image; detecting a second operation of the camera indicated by the user; and displaying a second image in the viewfinder frame in response to the second operation, where the second image is an image obtained by processing N frames of raw images captured by the camera; a neural network model is applied to a processing process, and the neural network model uses an image whose noise is lower than a target threshold as an output objective; and N is an integer greater than or equal to 2.

Abstract: This application relates to the field of image processing technologies, and provides a photographing method and apparatus for intelligent framing recommendation, to automatically match an appropriate framing recommendation solution for a user according to an algorithm, so that imaging quality is improved. The method includes: An electronic device obtains at least one framing recommendation result based on images captured by at least two cameras with different focal lengths, where the framing recommendation result includes a framing recommendation frame, and the framing recommendation frame indicates a framing recommendation effect of image photographing; and displays a target image based on a framing recommendation result selected by a user, where the target image is an image obtained through cropping, based on the framing recommendation result, the images captured by the at least two cameras.

Abstract: A method for detecting a complexity of a traveling scenario of a vehicle includes obtaining a travelling speed of the vehicle and a travelling speed of a target vehicle, determining, based on the traveling speed of the vehicle and the traveling speed of the target vehicle, a dynamic complexity of a traveling scenario in which the vehicle is located, determining static information of each static factor in the traveling scenario in which the vehicle is currently located, obtaining, based on the static information of each static factor, a static complexity of the traveling scenario in which the vehicle is located, and obtaining, based on the dynamic complexity and the static complexity, a comprehensive complexity of the traveling scenario in which the vehicle is located.

Abstract: This application discloses an image processing method and apparatus, and relates to the field of image processing technologies, to help optimize a color, a contrast, or a dynamic range of an image, so that an optimized image can be more objective, and robustness is improved. The method is applied to a terminal including a first camera and a second camera. The method includes: when an ISO of the first camera in a current photographing environment is greater than a first threshold, capturing a first image for a first scenario in the current photographing environment; capturing a second image for the first scenario; and optimizing the first image based on the second image to obtain a third image. An image style of the second image is better than that of the first image.

Abstract: This application discloses a photographing method and apparatus, to overcome blurring that occurs during photographing. When a zoom ratio is greater than a first zoom ratio threshold, a long-focus camera is started to capture an image. A zoom ratio of the long-focus camera is greater than or equal to the first zoom ratio threshold. Because a high zoom ratio causes large shake, a rotational blur occurs in the image. According to the photographing method disclosed in this application, a first neural network model for rotational image deblurring is used to implement rotational image deblurring processing. In this way, high imaging quality of an image, a video, or a preview image is presented to a user to some extent, and the imaging effect may not be inferior to the effect of photographing with a tripod.

Abstract: An image processing method includes obtaining N frames of images, determining one of the N frames of images as a reference image, where the other N?1 frames of images are to-be-processed images, obtaining N?1 frames of ghost-free images based on the N?1 frames of to-be-processed images, and performing an averaging operation on the reference image and the N?1 frames of ghost-free images, to obtain a first target image.

Abstract: An image processing method includes obtaining a plurality of frames of raw images. After preprocessing such as image alignment, channel splitting or pixel rearrangement is performed on the obtained plurality of frames of raw images, detail restoration is performed on an image based on a deep learning network, and luminance enhancement and color enhancement are performed on an image output by the deep learning network. A plurality of types of processing related to detail restoration are integrated into a same deep learning network.

Abstract: An image display method and device are provided. The method is applied to an electronic device having a display screen and a camera. The method includes: detecting a first operation of turning on the camera by a user; displaying a photographing interface on the display screen in response to the first operation, where the photographing interface includes a viewfinder frame including a first image; detecting a second operation of the camera indicated by the user; and displaying a second image in the viewfinder frame in response to the second operation, where the second image is an image obtained by processing N frames of raw images captured by the camera; a neural network model is applied to a processing process, and the neural network model uses an image whose noise is lower than a target threshold as an output objective; and N is an integer greater than or equal to 2.

Abstract: The present disclosure discloses a method for image or video shooting. The method is applied to a terminal that includes a first camera, a second camera, and a third camera. The second camera is a black-and-white camera, and the first camera, the second camera, and the third camera are cameras using prime lenses. The third camera is a color camera using a tele-photo lens. The method includes determining at least one camera from the first camera, the second camera, and the third camera based on a target zoom ratio as a target camera. The method further includes capturing, by using the target camera, at least one image that includes a target scene. The method further includes obtaining an output image of the target scene based on the at least one image that includes the target scene. According to the present disclosure, an approximately 5× lossless zoom effect is achieved.

Abstract: The present disclosure discloses a method for image or video shooting. The method is applied to a terminal that includes a first camera, a second camera, and a third camera. The second camera is a black-and-white camera, and the first camera, the second camera, and the third camera are cameras using prime lenses. The third camera is a color camera using a tele-photo lens. The method includes determining at least one camera from the first camera, the second camera, and the third camera based on a target zoom ratio as a target camera. The method further includes capturing, by using the target camera, at least one image that includes a target scene. The method further includes obtaining an output image of the target scene based on the at least one image that includes the target scene. According to the present disclosure, an approximately 5x lossless zoom effect is achieved.

Abstract: The present invention discloses an image processing method and apparatus, and a device. The method includes: obtaining N frames of images; determining one of the N frames of images as a reference image, where the other N-1 frames of images are to-be-processed images; obtaining N-1 frames of ghost-free images based on the N-1 frames of to-be-processed images; and performing an averaging operation on the reference image and the N-1 frames of ghost-free images, to obtain a first target image. The method can provide a snapshot mode for a camera, so that a user can snap a sharp image in different scenes, thereby improving user experience.