Abstract:
A method for evaluating color differences of pixels is provided. The method comprises obtaining color information of a first pixel in a color opponent space obtaining color information of a second pixel in the color opponent space, defining a half-line in the color opponent space based on the color information of the first pixel, and determining distance between color information of the second pixel and half-line in the color opponent space.
Abstract:
A method for inverse tone mapping is provided. The method comprising obtaining a digital image in a color space wherein the luminance is separate from the chrominance, determining a base luminance of pixels in the digital image, determining a detail enhancement map, determining a pixel expansion exponent map, determining an edge map of the image, inverse tone mapping luminance of image based on edge map, pixel expansion map and base luminance, and providing an expanded dynamic range image based on the inverse tone mapped luminance.
Abstract:
An image processing method is described. The method includes obtaining low dynamic range expansion exponents ELDR(p), obtaining target expansion exponents ET(p) as a weighted sum of the high dynamic range expansion exponents EHDR(p) and of the low dynamic range expansion exponents ELDR(p), applying obtained target expansion exponent ET(p) to low dynamic range luminance values YLDR of a low dynamic range version of the image, resulting in target luminance values YT, and building a tone-adapted version of said image based on said target luminance values YT.
Abstract:
Inverse tone mapping based on luminance zones is provided. A digital image can be obtained and luminance values of pixels of the digital image can be determined. One or more values of luminance zone boundaries can be determined. A zone expansion exponent map based on the luminance values and the one or more luminance zone boundaries can be determined. The one or more luminance zone boundaries divide the zone expansion exponent map into a plurality of luminance zones. The luminance values of the image can be inverse tone mapped based on the zone expansion exponent map. An expanded dynamic range image can be provided based on the inverse tone mapped luminance values.
Abstract:
A method for converting a standard dynamic range (SDR) sequence into a high dynamic range (HDR) sequence is described. The method includes determining (S1) successive shots in the SDR sequence by cut detection, detecting (S2) if the SDR sequence comprises a sub-sequence of at least two successive short shots having a duration lower than D1, said subsequence comprising at least one bright shot having a luminance and a size greater than L1 and SZ1 respectively, and mapping (S3) the luminance range of bright shots of the detected subsequence from the low dynamic range to a first high dynamic range and mapping the other shots of the SDR sequence from the standard dynamic range to a second high dynamic range in order to generate the HDR sequence, the first high dynamic range having a maximal value Lmax1 lower than that of the second high dynamic range Lmax2.
Abstract:
The disclosure relates generally to the field of high dynamic range (HDR) imaging and addresses the way of expanding the dynamic range of low dynamic range images. A method having the steps of obtaining expansion exponent map data for each one of a plurality of clusters of reference images, obtaining, for each cluster, one feature, called visual feature, representative of the luminance of reference images of the cluster, obtaining a visual feature for the image, comparing the visual feature of the image with the visual features of the clusters according to a distance criterion, selecting the cluster, the visual feature of which is the closest to the visual feature of the image, and applying an expansion exponent map defined by the expansion exponent map data of the selected cluster to the image is described.
Abstract:
A method for evaluating color differences of pixels is provided. The method comprises obtaining color information of a first pixel in a color opponent space obtaining color information of a second pixel in the color opponent space, defining a half-line in the color opponent space based on the color information of the first pixel, and determining distance between color information of the second pixel and half-line in the color opponent space.
Abstract:
The method comprises the steps of, successively for each image following a preceding image, based on a map of motion vectors that corresponds to the motion from said preceding image toward said following image, building a pixel mask for said following image, applying said pixel mask to the corresponding following image in order to obtain a corresponding masked image that samples the pixels of said following image. The application of this method to color clustering allows the iterative update of the colors clusters with limited computer resources.
Abstract:
Method comprising: first mapping, in a reference color space, said source colors from a source color gamut into a reference color gamut, resulting in intermediate colors, second mapping said intermediate colors from said reference color gamut into said target color gamut, resulting in target colors forming at least one mapped image, wherein said first mapping is defined through information representing said second mapping.
Abstract:
The method comprises segmenting lines into regions of saturated pixels, and, for each of these saturated regions, selecting at least one color channel that is not saturated, then, for each pixel of said region, adding to the color information provided by the saturated color channel for said pixel a difference between the color information provided by the selected non-saturated color channel for said pixel and a baseline color value computed for the region of this pixel.