An image processing method is provided. In the method, a target video frame set is acquired from video data of a plurality of video frames. The target video frame set includes a subset of the video frames that is selected based on characteristics of the subset of the video frames. A global color feature of a reference video frame is acquired. An image semantic feature of the reference video frame is acquired. An enhancement parameter of the reference video frame is acquired for each of at least one image information dimension according to the global color feature and the image semantic feature. Image enhancement is separately performed on the video frames in the target video frame set according to each enhancement parameter of the reference video frame to obtain target image data for each of the video frames in the target video frame set.

A system and method for image processing are provided. A pre-processed image may be obtained. The pre-processed image may be decomposed into a low-frequency image and a high-frequency image. At least one grayscale transformation range may be determined based on the low-frequency image. At least one grayscale transformation parameter may be determined based on the at least one grayscale transformation range. The low-frequency image may be transformed based on the at least one grayscale transformation parameter to obtain a transformed low-frequency image. A transformed image may be generated by reconstructing the transformed low-frequency image and the high-frequency image.

Devices, methods, and computer-readable media are disclosed describing an adaptive approach for image bracket selection and fusion, e.g., to generate low noise and high dynamic range (HDR) images in a wide variety of capturing conditions. An incoming image stream may be obtained from an image capture device, wherein the incoming image stream comprises a variety of differently-exposed captures, e.g., EV0 images, EV− images, EV+ images, long exposure (or synthetic long exposure) images, EV0/EV− image pairs, etc., which are received according to a particular pattern. When a capture request is received, a set of rules and/or a decision tree may be used to evaluate one or more capture conditions associated with the images from the incoming image stream and determine which two or more images to select for a fusion operation. A noise reduction process may optionally be performed on the selected images before (or after) the registration and fusion operations.

An image processing method and a device configured to implement the same are disclosed. The method comprises: obtaining optical input from a hybrid imaging device, wherein an obtained optical input comprises a first component and a second component that temporally corresponds to the first component; wherein the first component of the obtained optical input corresponds to a first temporal resolution, while the second component of the obtained optical input corresponds to a second temporal resolution higher than that of the first component; performing image restoration operation on a first subset of the first component of the obtained optical input in accordance with data from the second component of the obtained optical input; and performing image fusion operation to generate fused image data from an output of the image restoration operation and a second subset of the first component of the obtained optical input.

A piecewise linear function for image tone conversion is easily corrected. An image processing apparatus first obtains a piecewise linear function for image tone conversion. Next, the image processing apparatus performs correction, in a case where the magnitude of the slope of the piecewise linear function in a processing target piece is larger than a predefined upper limit value, on the piecewise linear function so as to bring the magnitude of the slope of the piecewise linear function in the processing target piece to the upper limit value by changing the value of the end point of the processing target piece. The image processing apparatus performs the correction sequentially on a piece adjacent to the processing target piece.

Disclosed is a display apparatus. The display apparatus obtains first characteristic information, which is provided according to a plurality of sections of content and corresponds to an image characteristic of a section to be displayed among the plurality of seconds, from a signal received in the signal receiver, obtains first image-quality setting information for setting image quality of the section based on the obtained first characteristic information, obtains second characteristic information corresponding to an image characteristic of a frame included in the section from the frame, obtains second image-quality setting information for setting image quality of the frame based on the obtained first image-quality setting information and the obtained second characteristic information, and controls the display to display an image of the frame, the image quality of the frame being set based on the obtained second image-quality setting information.

The various embodiments of the present disclosure are directed towards methods for tone mapping High-Dynamic-Range (HDR) image data, as well as controlling the brightness of the image encoded by HDR the image data and/or the tone-mapped image data. HDR image is captured. A tone mapping function for the HDR image data is generated. To generate the tone mapping function, control points are dynamically determined based on an analysis of the HDR image data. The tone mapping function is fit to the control points. The tone mapping function is a non-linear function, and is described by a curve in a plane. The shape of the curve is constrained by a line generated from a portion of the control points. The tone mapping function is applied to the HDR image data. A color-compression is applied to the tone mapped image data to generate Standard Dynamic Range or Low Dynamic Range image data.

A method for inverse tone mapping includes obtaining a histogram of a low dynamic range image, called LDR image and obtaining an ITMO function, allowing obtaining a pixel value of a High Dynamic Range image, called HDR image, from a pixel value of the LDR image and a gain function depending on said pixel value of the LDR image. A search process is applied using the obtained histogram to identify areas of the LDR image producing bright areas in the HDR image when the ITMO function is applied on said LDR image. Information representative of the bright areas is used to determine when modifying the gain function to ensure the HDR image respects at least one predefined light energy constraint.

Disclosed in the present application are an image acquisition method, an imaging apparatus, an electronic device, and a non-transitory computer-readable storage medium. The image acquisition method includes: controlling exposure of a pixel array; and performing an interpolation process on a first colored original image and a second colored original image according to a first panchromatic original image, and fusing an interpolated image and the first panchromatic original image to obtain a target image with same resolution as resolution of the pixel array.

The current disclosure provides for mapping medical images to style transferred medical images using deep neural networks, while maintaining clinical quality of the style transferred medical image, thereby enabling a clinician to evaluate medical images in a preferred style without loss of clinically relevant content. In one embodiment the current disclosure provides for a method comprising, acquiring a medical image of an anatomical region of a subject, wherein the medical image is in a first style, selecting a target style, wherein the target style is distinct from the first style, selecting a clinical quality metric, selecting a trained style transfer network based on the target style and the clinical quality metric, mapping the medical image to a style transferred medical image using the trained style transfer network, wherein the style transferred medical image is in the target style, and displaying the style transferred medical image via a display device.