A system is provided for generating video content with hue-preservation in virtual production. The system comprises a memory for storing instructions and a processor configured to execute the instructions. Based on the executed instructions, the processor is further configured to control a saturation of scene linear data based on mapping of a first color gamut corresponding to a first encoding format of raw data to a second color gamut corresponding to a defined color space. The processor is further configured to determine a standard dynamic range (SDR) video content in the defined color space based on the scene linear data. Based on a scaling factor that is applied to three primary color values that describe the first color gamut, hue of the SDR video content is preserved.

A color correspondence information generating system includes an object database that stores correspondences between recognition information and color characteristic information about first objects recognized by the recognition information; an object recognition section that recognizes the first objects in the first image from the first image and the recognition information, and outputs image regions of the first objects in the first image and first color characteristic information; and a color correspondence information generation section that generates the color correspondence information using the color information and the first color characteristic information of pixels in the image regions. The color characteristic information and the recognition information have a one-to-one correspondence relation with each other, or the color characteristic information is the recognition information itself.

An imaging device may have an array of image pixels that includes red, green, blue, and infrared pixels. The imaging device may include a dual-band filter that allows transmission of light in the visible band and in the near-infrared band and may include color processing circuitry that produces a color image with marked infrared regions. The color processing circuitry may include a standard color processing pipeline with a color correction matrix that produces a tone-mapped standard red, green, and blue image and may include infrared marking circuitry. The infrared marking circuitry may include hue angle determination circuitry, cell means determination circuitry, and near-infrared determination circuitry that determine portions of the image with high infrared reflectance to be marked. The infrared-marked tone-mapped standard red, green, and blue image may be output to a machine vision system to identify objects in the imaged scene with high infrared reflection.

To allow a better determination of an image of a different luminance dynamic range (in particular as characterised by a different maximum luminance a.k.a. peak brightness) than an input image, the present application teaches several variants of a luminance processor (501) arranged to calculate an output luminance of a pixel of an output image (Im_LDR; Im3000nit) having a second luminance dynamic range characterized by a second peak brightness (PB_LDR; PB_MDR) from an input luminance of a spatially collocated pixel of an input image (MAST_HDR) having a first luminance dynamic range characterized by a first peak brightness (PB_HDR), characterized in that the luminance processor comprises: a gain calculation unit (514) arranged to calculate a multiplication factor (gL) being a function of the input luminance and a luminance mapping function (FLM); a maximum calculation unit (601) arranged to calculate a strength value (V) which is the maximal one of the three red, green and blue color components of the color of the pixel of the input image, wherein those components are either linear red, green and blue color components or a power of those linear red, green and blue color components; an overflow calculator (602) arranged to calculate an overflow measure (T) indicating how close to the upper gamut boundary the output luminance is; a gain factor modification unit (603) arranged to determine an alternative gain factor (F1(gL)) in case the overflow measure is larger than a threshold (G), and arranged to keep the original gain factor otherwise, and arranged to output one of those as a final gain factor (gF); and a multiplier (530) to multiply the input color (R′G′B′_nrm) by the final gain factor (gF) to obtain an output color (R′G′B′_HDR) having the output luminance.

A controlling value is calculated using a first white balance gain and a second white balance gain. Using the calculated controlling value, an image processing parameter is then modulated. Using this modulated image processing parameter, image data processing is performed, and storage, transmission, and the like of the image processing parameter are performed. This can realize advanced image processing reflective of the white balance gain.

An image processing apparatus includes a detection unit configured to detect a specific area from a captured image, and a determination unit configured to determine, based on the detected specific area, a light source color including a characteristic color by using a learning unit trained in advance by machine learning.

An imaging system can obtain image data, for instance from an image sensor. The imaging system can supply the image data as input data to a machine learning system, which can generate one or more maps based on the image data. Each map can identify strengths at which a certain image processing function is to be applied to each pixel of the image data. Different maps can be generated for different image processing functions, such as noise reduction, sharpening, or color saturation. The imaging system can generate a modified image based on the image data and the one or more maps, for instance by applying each of one or more image processing functions in accordance with each of the one or more maps. The imaging system can supply the image data and the one or more maps to a second machine learning system to generate the modified image.

An image correction device includes a reception unit, a detection unit and a correction unit. The reception unit receives a first-image and a second-image, which are obtained by a first-imaging device and a second-imaging device, and an imaging condition that is at least one piece of information on an imaging date and time or information on an imaging location corresponding to each of the first-image and the second-image. The detection unit detects the same scene between images indicated by the first-image and the second-image based on the imaging conditions corresponding to each of the first-image and the second-image. The correction unit extracts, from each of the images indicated by the first-image and the second-image corresponding to the same scene, a common subject which is common between the images, and performs, on the corresponding image, color correction of making colors of the extracted common subject similar to each other.

To allow a better determination of an image of a different luminance dynamic range (in particular as characterised by a different maximum luminance a.k.a. peak brightness) than an input image, the present application teaches several variants of a luminance processor (501) arranged to calculate an output luminance of a pixel of an output image (Im_LDR; Im3000 nit) having a second luminance dynamic range characterized by a second peak brightness (PB_LDR; PB_MDR) from an input luminance of a spatially collocated pixel of an input image (MAST_HDR) having a first luminance dynamic range characterized by a first peak brightness (PB_HDR), characterized in that the luminance processor comprises: a gain calculation unit (514) arranged to calculate a multiplication factor (gL) being a function of the input luminance and a luminance mapping function (FLM); a maximum calculation unit (601) arranged to calculate a strength value (V) which is the maximal one of the three red, green and blue color components of the color of the pixel of the input image, wherein those components are either linear red, green and blue color components or a power of those linear red, green and blue color components; an overflow calculator (602) arranged to calculate an overflow measure (T) indicating how close to the upper gamut boundary the output luminance is; a gain factor modification unit (603) arranged to determine an alternative gain factor (F1(gL)) in case the overflow measure is larger than a threshold (G), and arranged to keep the original gain factor otherwise, and arranged to output one of those as a final gain factor (gF); and a multiplier (530) to multiply the input color (R′G′B′_nrm) by the final gain factor (gF) to obtain an output color (R′G′B′_HDR) having the output luminance.

A system accesses an image with each pixel of the image having luminance values each representative of a color component of the pixel. The system generates a first histogram for aggregate luminance values of the image, and accesses a target histogram for the image representative of a desired global image contrast. The system computes a transfer function based on the first histogram and the target histogram such that when the transfer function is applied, a histogram of the modified aggregate luminance values is within a threshold similarity of the target histogram. The system modifies the image by applying the transfer function to the luminance values of the image to produce a tone mapped image, and outputs the modified image.