Interdigital Vc Holdings, Inc.

Thomson Licensing

Interdigital Ce Patent Holdings

Tania Pouli

Jonathan Kervec

Laurent Cauvin

Hassane Guermoud

Christel Chamaret

Dominique Thoreau

Jurgen Stauder

Sylvain Thiebaud

Cedric Thebault

Erik Reinhard

Marie-Jean Colaitis

Ronan Boitard

Kadi Bouatouch

Guillaume Poirier

Mekides Assefa Abebe

Mekides Abebe

Chaker Larabi

Rémi Cozot

Dmitry Kuzovkin

A lower dynamic range visual content () of a virtual reality or VR scene represented in a curved shape form is adapted to a higher dynamic range display of the virtual reality scene. At least two planar key views () of the VR scene area obtained at least two parameter values () respectively associated with those planar key views are obtained, corresponding to at least one parameter adapted to expand a dynamic range of a visual content, and a higher dynamic range visual content () corresponding to the lower dynamic range visual content in at least part of the VR scene extending beyond the planar key views is determined, based on the parameter values. Applications to Inverse Tone Mapping.

Device and method for dynamic range expansion in a virtual reality scene

According to the invention, the saturation thresholds (th; th; th) used for this detection depend on color coordinates (r, g, b) representing an illuminant (ILL) of the image.

Method for detection of saturated pixels in an image

The present disclosure involves expanding the dynamic range of low dynamic range images and concerns obtaining a first expansion exponent map for an image, and determining, for each pixel of the image, an expanded luminance value by performing an exponentiation with an expansion exponent value determined from the first expansion exponent map on a luminance value of the pixel, and can include calculating, for the pixel of the image, an expansion correcting value by using a modulating function that takes as input a value representative of the luminance of the pixel and is an increasing function whose increase is higher for higher input values, and subtracting the expansion correcting value from the expansion exponent value of the first expansion exponent map.

Inverse tone mapping method and corresponding device

The present disclosure relates to a method for providing assistance to a colorist in color grading of a virtual reality video content, called VR content. The method includes receiving the VR content being graded by a color grading station and receiving position information representative of the position of at least one hand of a colorist versus the color grading station. The method further includes generating, based on the position information, visual control information showing the position of the at least one hand of the colorist versus at least one grading control element of the color grading station and displaying the visual control information together with the graded VR content on a head mounted display carried by the colorist in order to help the colorist manipulating the at least one grading control element.

Method and system for color grading a virtual reality video content

For the processing of an image with a tone-mapping function, it is known to select a tone-mapping function among a reference collection of reference tone-mapping functions and to apply the selected tone-mapping function to colors of this image. When applying this method to images of a video content, it is proposed to add, after such a selection for an image, a step of validation of this selection for the next images of video content. Advantage: prevent too frequent changes of tone-mapping function inside a video content, lower temporal instabilities and visual discomfort during visualization.

Tone-mapping of colors of a video content

A lower dynamic range visual content () of a virtual reality or VR scene represented in a curved shape form is adapted to a higher dynamic range display of the virtual reality scene. At least two views planar key views () of the VR scene area obtained, at least two parameter values () respectively associated with those planar key views are obtained, corresponding to at least one parameter adapted to expand a dynamic range of a visual content, and a higher dynamic range visual content () corresponding to the lower dynamic range visual content in at least part of the VR scene extending beyond the planar key views is determined, based on the parameter values. Applications to Inverse Tone Mapping.

The module () comprises: &#x2014;a low pass filter for low pass filtering luminance component of the image, &#x2014;a first look up table () storing precomputed values of a first expansion function of only low pass filtered luminance values, &#x2014;a second look up table () storing precomputed values of a second expansion function of only luminance values, &#x2014;a processor () configured to multiply an output of the second look up table corresponding to an input luminance value of a color to expand by an output of said first look up table corresponding to an input low pass filtered luminance value associated with said input luminance value.

Low cost color expansion module for expanding colors of an image

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.

Method and apparatus for inverse tone mapping

An image processing method is described. The method includes obtaining low dynamic range expansion exponents E(p), obtaining target expansion exponents E(p) as a weighted sum of the high dynamic range expansion exponents E(p) and of the low dynamic range expansion exponents E(p), applying obtained target expansion exponent E(p) to low dynamic range luminance values Yof a low dynamic range version of the image, resulting in target luminance values Y, and building a tone-adapted version of said image based on said target luminance values Y.

Method for tone adapting an image to a target peak luminance Lof a target display device

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.

Inverse tone mapping based on luminance zones

A method and device for processing LDR images of a video sequence to improve image quality. The method comprises temporally decomposing successive HDR frames of a video sequence and the corresponding LDR frames and performing a comparison between the HDR and LDR frequency sub-bands. A current LDR image can then be modified on the basis of a comparison between the frequency sub-bands.

Method and device for processing images

Systems and methods of re-coloring digital images are disclosed. A system including a processor and a memory can execute stored instructions to obtain luminance information of a first image, e.g., an original grayscale image, and obtain color information of a second image, e.g., a colorized image of the original grayscale image. Multiple segmented image regions can be determined based on the luminance information of the first image. A color seed for each segmented image region can be determined based on the color information of the second image. A third image, e.g., a re-colored image, can be determined based on diffusing the color seeds of the segmented image regions.

Methods and systems for color processing of digital images

The present principles relate to a method and a device for reducing noise in a component of a picture. The method includes obtaining a low-pass filtered component by low-pass filtering the component of the picture, for a current pixel in the component of the picture. For at least one current neighboring pixel of the current pixel, computing a distance, relative to the current neighboring pixel, between the value of the current pixel in the low-pass filtered component and the value of the current neighboring pixel in the low-pass filtered component. When the distances relative to the at least one neighboring pixels of the current pixel are lower than a first threshold, modifying the value of the current pixel in said component of the picture according to a linear combination of the value of the current pixel in the component of the picture and the value of the current pixel in the low-pass filtered component. Otherwise the value of the current pixel in the at least one component of the picture remains unchanged.

Method and device for reducing noise in a component of a picture

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.

Method for conversion of a saturated image into a non-saturated image

Method comprising, for each pixel, obtaining a pixel expansion exponent value (E'(p)) by low pass filtering luminance values of colors of pixels in its spatial neighborhood, obtaining a pixel luminance-enhancement value (Y(p)) by extraction of high frequencies of luminance values of colors of pixels in its spatial neighborhood, and then inverse tone mapping the luminance (Y(p)) according to the equation Y(p)=Y(p)&#xd7;[Y(p)].

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Le Rheu, France

Tania Pouli