The present disclosure relates generally to the field of video processing, and more particularly, to high dynamic range (HDR) image processing. In particular, the present disclosure relates to a method for determining a parameter set for a tone mapping curve. The method comprises obtaining a plurality of parameter sets, wherein each parameter set defines the tone mapping curve, and wherein each parameter set is derived based on one of a plurality of HDR video frames. Further, the method comprises temporally filtering the plurality of parameter sets to obtain a temporally filtered parameter set.

A method of reducing noise in an input image by setting, as a local window among color pixels included in the input image, a target pixel and neighboring pixels adjacent to the target pixel, determining color pixel values for the target pixel and each of the neighboring pixels included in the local window, generating local color average values are generated by averaging, color by color, the color pixel values, generating offset color pixel values by converting the color pixel values of the target pixel and the neighboring pixels based on the local color average values, and generating a compensated color pixel value of the target pixel by adjusting the color pixel value of the target pixel based on the offset color pixel values.

A method and apparatus for capturing digital video includes displaying a preview of a field of view of the imaging device in a user interface of the imaging device. A sequence of images is captured. A main subject and a background in the sequence of images is determined, wherein the main subject is different than the background. A sequence of modified images for use in a final video is obtained, wherein each modified image is obtained by combining two or more images of the sequence of images such that the main subject in the modified image is blur free and the background is blurred. The sequence of modified images is combined to obtain the final video, which is stored in a memory of the imaging device, and displayed in the user interface.

A method for analyzing neuropharmacology of a drug, including the steps of providing a set of brain activity maps representing changes of a brain activity of a living species under an influence of a plurality of known drugs each consisting of a known chemical structure; clustering the set of brain activity maps to form a plurality of functional classifiers; and classifying a brain activity map associated with a chemical compound using the functional classifiers so as to predict a neuropharmacology of the chemical compound.

An apparatus and method are described for a non-uniform rasterizer. For example, one embodiment of an apparatus comprises: a graphics processor to process graphics data and render images using the graphics data; and a non-uniform rasterizer within the graphics processor to determine different resolutions to be used for different regions of an image, the non-uniform rasterizer to receive a plurality of polygons to be rasterized and to responsively rasterize the polygons in accordance with the different resolutions.

A method of processing image data for an image, the image data including colour data expressed in a first colour space, transforms the colour data to a luminance-normalised colour space, and performs one or more image processing operations on the transformed colour data to generate processed image data.

An image processing device (1) includes an exposure control unit (102), a Δ pose estimating unit (109), and an integration unit (111). The exposure control unit (102) controls exposure by sequentially performing positive correction of increasing exposure from proper exposure or negative correction of decreasing exposure from the proper exposure as the exposure at a time of acquiring each of a plurality of image frames in time series in a predetermined execution order. The Δ pose estimating unit (109) estimates first position pose of the image processing device based on matching between image frames subjected to the positive correction and second position pose of the image processing device based on matching between image frames subjected to the negative correction. The integration unit (111) integrates the first position pose and the second position pose.

A method of reading a medical image by a computing device operated by at least one processor is provided. The method includes obtaining an abnormality score of the input image using an abnormality prediction model, filtering the input image so as not to be subsequently analyzed when the abnormality score is less than or equal to a cut-off score based on the cut-off score which makes a specific reading sensitivity; and obtaining an analysis result of the input image using a classification model that distinguishes the input image into classification classes when the abnormality score is greater than the cut-off score.

Local detail enhancement (LDE) is an imagery contrast enhancement method applied to visible and uncooled long wave imagery. It enhances local spatial detail through the use of a median based high/band pass filter. The generated detail channel is blended with a histogram-equalized version of the image, creating an image that contains both local detail as well as retaining some amount of global intensity. Retaining global intensity coherency allows for easier target acquisition when compared to fully local forms of contrast enhancement.

Provided is an image acquisition apparatus including an image sensor configured to obtain an image, and a processor configured to obtain a basis based on a surrounding environment of the image acquisition apparatus, estimate illumination information based on the obtained basis, and perform color conversion on the image based on the estimated illumination information.