Classifications

• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T5/00—Image enhancement or restoration
  • G06T5/90—Dynamic range modification of images or parts thereof
  • G06T5/92—Dynamic range modification of images or parts thereof based on global image properties
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T7/00—Image analysis
  • G06T7/90—Determination of colour characteristics
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
  • H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
  • H04N1/40—Picture signal circuits
  • H04N1/407—Control or modification of tonal gradation or of extreme levels, e.g. background level
  • H04N1/4072—Control or modification of tonal gradation or of extreme levels, e.g. background level dependent on the contents of the original
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
  • H04N5/00—Details of television systems
  • H04N5/14—Picture signal circuitry for video frequency region
  • H04N5/20—Circuitry for controlling amplitude response
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
  • H04N5/00—Details of television systems
  • H04N5/44—Receiver circuitry for the reception of television signals according to analogue transmission standards
  • H04N5/57—Control of contrast or brightness
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T2207/00—Indexing scheme for image analysis or image enhancement
  • G06T2207/10—Image acquisition modality
  • G06T2207/10024—Color image
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T2207/00—Indexing scheme for image analysis or image enhancement
  • G06T2207/20—Special algorithmic details
  • G06T2207/20172—Image enhancement details
  • G06T2207/20208—High dynamic range [HDR] image processing
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
  • H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
  • H04N1/46—Colour picture communication systems
  • H04N1/56—Processing of colour picture signals
  • H04N1/60—Colour correction or control
  • H04N1/6027—Correction or control of colour gradation or colour contrast
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
  • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
  • H04N23/80—Camera processing pipelines; Components thereof
  • H04N23/84—Camera processing pipelines; Components thereof for processing colour signals
  • H04N23/86—Camera processing pipelines; Components thereof for processing colour signals for controlling the colour saturation of colour signals, e.g. automatic chroma control circuits

Definitions

• the invention relates to apparatuses and methods and resulting products like data storage or transmission products or signals, for converting an image with pixel colors with first luminances into an image with pixel colors with second, lower or higher luminances.
• a useful category of color mappings is one in which the luminance of a pixel color changes, yet the intrinsic color itself, which can be characterized e.g. with a chromaticity like CIE 1976 (u',v'), is the same for the resultant output color and the to be processed input color.
• This is in fact the color mapping corresponding to lighting changes in nature: illuminating an object spectrum with more light having a light spectrum, produces colors with an increasing luminance (or another luminance correlate like e.g. a luma after conversion to this correlate) yet with the same chromaticity.
• This kind of processing for a technology which has recently become important namely dynamic range mapping for image(s) and video.
• PB peak brightness
• LDR low dynamic range
• a HDR image which is an image which may typically have object pixel luminances which have a luminance ratio of at least 1000: 1, and typically a luminance distribution with both a significant amount of bright pixels, and a significant amount of dark pixels, i.e. approximately a thousand times darker than the bright ones
• an LDR image may have objects which look undesirably bright when directly rendered on a display of say 3000 nit PB.
• HDR grading image of a captured (or computer generated) scene which corresponds to a HDR reference monitor, and is suitable for being rendered on displays of higher PB (than e.g. 1000 nit, or an associated minimum usable PB), to an LDR image, associated with an LDR reference monitor (and the dynamic ranges of the images, or more precisely their associated reference monitors, are different by a factor of at least 1.5, in other words approximately at least one stop or factor 2, but it may also be e.g. a factor 4 or 10 or larger).
• LDR may use e.g. the legacy Rec. 709 gamma-type EOTF
• HDR image(s)/video may typically be encoded according to an EOTF which has at least partially an exponential (inverse logarithmic) character in its functional shape definition, e.g. following human vision characteristics like a Barten contrast sensitivity function.
• HDR image not necessarily has a larger amount of bits per color component than an LDR image. They may both be defined in e.g. a 3x10 bits RGB format (which can be interpreted as a [0-1.0]-scaled component definition, which we assume will be the codification of images before color mapping whatever the original and final format for the result to be transmitted are), the difference only residing in how the encoded colors have to be interpreted, i.e. according to the luminance or luma distribution defined with the given respective EOTF (and optimally color graded to yield the good corresponding look, i.e. with different object luminances for the same objects in both gradings).
• RGB format which can be interpreted as a [0-1.0]-scaled component definition, which we assume will be the codification of images before color mapping whatever the original and final format for the result to be transmitted are
• Applicant has created a coding system, which allows one to encode at least two (or more) gradings of a scene, one typically being an LDR grading, and a second one being of higher dynamic range which is typically an HDR grading.
• the encoding works by encoding one of the two gradings as an actual image, which typically can be done by using classical video encoding containers, from a video coding standard like e.g. MPEG- HEVC.
• the data is reformatted in a non-compliant manner, e.g.
• Fig. 1 shows an example of such an encoding apparatus 100.
• An image source 120 say a hard disk delivers an input image Im Rl of a first luminance dynamic range, say a HDR grading (a grading being a determination of the object luminances in the image so that to the creating artists they look correct when rendered on the associated reference display, the PB of which is typically co-encoded with the image as image-kind describing metadata).
• a color mapper 121 the grader can chose via user data UI from e.g. a color grading keyboard and in a grading software one or more functions and their parameters to derive a second graded image for each HDR image (i.e. Im Rl), say an LDR image.
• the encoder 101 represents this data as numbers according to a prescribed format, e.g. it makes DCT-based image components of Im_R2, and stores the functional metadata in SEI messages, or similar, and via a data output 130 sends it to a data communication technology 131 (which in the Figure is a BD disk e.g., but this can also be an internet server for VOD, etc.).
• a data communication technology 131 which in the Figure is a BD disk e.g., but this can also be an internet server for VOD, etc.
• the color mapper 200 may be a component of a decoder which calculates the original image(s) based on the received basic image and functional color mapping metadata of at least a luminance mapping function (F), but it may similarly be incorporated in an encoder, when the grader is still trying various possible functions F for the best look, and ultimately outputting the data for that best look over the data output 130.
• Maximum calculation unit 201 calculates which of the three components is for this pixel the highest, which may e.g. be the blue component if the object wherein the pixel resides is blue. This yields the maximum M.
• a predetermined function F (which realizes the dynamic range changing required color mapping, as far as the brightness part is concerned) is applied to M, yielding F(M).
• this function boosts the darkest colors, then keeps the middle colors approximately equal to their original values, and somewhat boosts the bright values again.
• brightness mapper 202 applies this function (which may be composed of partial functions, or realized as a LUT) to M.
• the scaling parameter calculator 203 calculates a scaling parameter a by dividing F(M) by M.
• a multiplier 204 uses this scaling parameter a to multiply it with each color component (R,G and B), yielding appropriately scaled color components (Rs, Gs, Bs).
• This is hence a powerful system which gives the grader great colorimetric control over the look of his images. It does come with a minor problem however. Although for many images the results are good, it can be seen that for some images there is a noisy problem.
• the problem occurs because the scaling parameter a picks up the noise in the dominant color component, and so becomes noisy itself.
• a relatively uniform area which is always a bad region for conspicuousness of noise
• the maximum component for all or most of those pixel will hence be the blue component, which may typically be noisy for several types of image.
• the M value will then jitter around a value of say 0.7.
• the functional mapping may correspond to a multiplication of say 3. But not only that, if there is a sharp discontinuity in the function F around 0.7, the higher M values may be boosted by 3 and the lower than 0.7 values may e.g. be multiplied by 1.
• the object of having a largely chromaticity-preserving luminance mapping with reduced noise sensitivity is realized by an image color processing apparatus (200) arranged to transform an input color (R,G,B) defined by a red, green and blue color component of a pixel of an input image (Im_R2) having a first luminance dynamic range into an output color (Rs, Gs, Bs) of a pixel of an output image (Im res) having a second luminance dynamic range, which first and second dynamic ranges differ in extent by at least a multiplicative factor 1.5, comprising:
• a maximum calculation unit (201) arranged to calculate the maximum (M) of at least three components of the input color
• a brightness mapper (202) arranged to apply a function (F) to the maximum, yielding an output value (F(M)), whereby the function is predetermined having a constraint that the output value for the highest value of the maximum (M) cannot be higher than 1.0;
• a scaling parameter calculator (203) arranged to calculate a scaling parameter (a) being equal to the output value (F(M)) divided by the maximum (M);
• a multiplier (204) arranged to multiply the red, green and blue color components of the input color (R,G,B) by the scaling parameter (a), yielding the color components of the output color,
• the color processing apparatus (200) comprises at least one component multiplier (303) arranged to multiply a component (B) of the input color with a weight (wB) being a real number yielding a scaled component (Bw) prior to input of that component in the maximum calculation unit (201), and wherein the at least three components comprise respective weighed or non- weighed functions of each of the red, green and blue color components.
• Weights will typically be between (inclusive) 0.0 and 1.0.
• the 3 or 4 inputs, or additional inputs may also be non-linear functions and/or combinations of the R,G,B color components. So one or more input component to the maximum calculator may be 1.0 and other components may have weights of other values, typically lower than 1.0. Where we say weighed functions, the reader should understand that the unity function also applies, and that a non-weighed unity function means the original e.g. red color component itself, but that at least one of the inputs should be weighed by a non-unity value before going through maximization.
• the scaling can then do a brightness processing which is similar to the linear re-lighting in nature., and the grader can design whatever brightness mapping function 205 he desires, e.g. to darken a corner of the room for a mood effect, and to increase the contrast of the grey values of e.g. a table and the objects on it.
• At least one of the input components can be weighed, before the brightness position of a color is judged with it.
• the coefficient of blue can be set low, e.g. 0.25 of even 0.1. This assures that the (weighed) blue component will seldomly be selected in the maximum operation, and e.g. the green one will be selected, which usually doesn't give problems.
• the color components are approximately equal, so it doesn't matter which one is selected.
• a cyan one may as well use its green component as its blue one, and reds would normally have the red component being the maximum, whatever the blue scaling factor. Only for some colors, like a pure blue (e.g. (0,0 128)*4) would the blue still be selected as the maximum component even for small wB, but those colors don't occur frequently, and then the noise problem may not be visually problematic.
• the weight factors may typically be preset by the grader for e.g. a scene in the movie, i.e. a shot of images with the same colorimetry, or even an entire movie, based on its capturing technology noise characteristics (the former per-scene approach has the advantage that the grader can handle the severity of the noise based on the type of color processing he wants to do on the scene, which may boost some noise severely, or not).
• the grader may look at the noise behavior and test a couple of weight settings with sliders, or he may be helped with an automatic weight setting algorithm based on the noise characteristics, and then fmetune.
• the automatic analysis may spot specific color regions which have a severe noise problem, and then flash them to point the grader's attention to them.
• Fig. 5 schematically shows an example of what could be a mapping to derive a LDR grading from a received HDR grading basic image (where the grader mainly decided to boost midrange contrast, and allow some clippings in the brights which may have been lamps).
• the grader mainly decided to boost midrange contrast, and allow some clippings in the brights which may have been lamps.
• the factor a can vary quite somewhat for the colors with Bl versus B2, and so even a region which should look reasonably uniform can pick up quite some noise pattern (which becomes visible because the noise in a relatively dark blue component gets leaked into the luminous green component, because the red and green components are multiplied by that same noisy factor).
• scaled blue components they will probably not be selected. If we have a slightly bluish bright whitish sky e.g., the green components of those pixels will have approximately the same values as Bl and B2, but the green component will be less noisy so there will be a smaller spread between possible selected maximum values Gl , G2, G3, ...
• the image color processing apparatus (200) comprises a multiplier for each of the three components of the input color, and the components being red, green and blue.
• a color representation which is linear RGB.
• the image color processing apparatus (200) obtains three weights (wR, wG, wB) from a data source associated with the input image (Im_R2).
• a grader may set the weights in software when looking at the characteristics of at least some images of a video, or the image if only a single still image is to be processed.
• a decoding side e.g. in a settopbox (STB)
• STB settopbox
• computer, television, digital cinema receiver in a movie theatre, etc. typically the weights have been determined, and the decoder reads them from a source.
• they may be stored as metadata on a BD disk or other memory product, may be received as data fields in a transmitted television signal, etc.
• the data may include a mathematical scheme to calculate some of the weights at a receiver, but normally one wants the results obtained at encoder and decoder to be the same.
• Advantageously embodiments of the image color processing apparatus (200) comprise a luminance calculation unit (306) arranged to calculate from the red, green and blue components a luminance as a fourth component of the input color, and comprising a luminance multiplier (304) arranged to multiply the luminance (Y) with a luminance weight (wY), yielding an output result which is input as a fourth input to the maximum calculation unit (201).
• a luminance calculation unit (306) arranged to calculate from the red, green and blue components a luminance as a fourth component of the input color, and comprising a luminance multiplier (304) arranged to multiply the luminance (Y) with a luminance weight (wY), yielding an output result which is input as a fourth input to the maximum calculation unit (201).
• the skilled person knows how to calculate the luminance as a linear combination of RGB color components with fixed factors, which depend on the colorimetry of the chosen representation, i.e. the chromaticities of the primaries, and the chosen white point. Doing a scaling based on the lumina
• weights of the color components can be set depending on where one wants them to take over in the maximum determination, e.g. at 0.5 or lower.
• Advantageously embodiments of the image color processing apparatus (200) comprise at least one non- linear function application unit (401) arranged to apply a nonlinear function to at least one of the red, green and blue color components, and wherein the maximum calculation unit (201) has as input besides the result (NR) of applying the non- linear function to the color component, at least two other color components which contain color information of the two of the red, green and blue components which were not selected for being processed by the at least one non-linear function application unit (401).
• This has several possible applications. On the one hand, it allows the grader to design a mapping function 205 not in a linear domain, but e.g. in a gamma domain. In that case, the three functions may apply e.g.
• Advantageous embodiments of the image color processing apparatus (200) contain a color analysis unit (410) arranged to analyze the input color, and determine therefrom the weights (wR, wG, wB) of at least the red, green and blue color components.
• a color analysis unit (410) arranged to analyze the input color, and determine therefrom the weights (wR, wG, wB) of at least the red, green and blue color components.
• the weights wR, wG, wB may for pixels fulfilling that condition be set to low values, so that the luminance comes out of the maximum.
• the weight of the blue component into the maximum calculator may be set considerably lower than 1.0, to a value predetermined in the laboratory, etc. Whether this is realized in an IC as one component with continuously updated weights, or a parallel passing to two components, one of which has e.g. fixed weights for processing the low saturation colors, is a mere matter of design.
• Advantageously embodiments of the image color processing apparatus (200) contain a color analysis unit (410) arranged to analyze the input color, and determine therefrom the functional shape of at least one of the at least one non-linear functions of the at least one non-linear function application unit (401).
• different functions can be chosen on colorimetric conditions of the color of the currently processed color.
• a linear scheme may be used in which the luminance always or usually wins in the maximum determination, in a color sector of strong blues, some non-linear function may be selected, which yields e.g. at least a blue non-linear input NB, etc.
• Advantageous variants are also e.g. a method of image color processing to transform an input color (R,G,B) of a pixel of an input image (Im_R2) having a first luminance dynamic range into an output color (Rs, Gs, Bs) of a pixel of an output image (Im res) having a second luminance dynamic range, which first and second dynamic ranges differ in extent by at least a multiplicative factor 1.5, comprising:
• At least one component of the at least three components is multiplied with a weight being a real number yielding a scaled component (Bw) as input for that maximum calculation.
• a weight being a real number yielding a scaled component (Bw) as input for that maximum calculation.
• real numbers may of course be represented, e.g. transmitted, as integers with a sufficient amount of bits, so that they can be converted into real numbers with sufficient precision.
• the precision of these weights may not be that critical and then 1% accuracy e.g. would be good.
• a method of image color processing in which the maximum is calculated from in addition to three red, green and blue color components also a luminance (Y) scaled with a luminance weight (wY).
• a method of image color processing as claimed in one of the above method claims in which at least one of the weights (wR, wG, wB, wY) is determined based on an analysis of the pixel color.
• a computer program product comprising code codifying the steps of at least one of the above method claims, thereby upon running enabling a processor to implement that method.
• An image signal (S im) comprising an encoding of colors of a matrix of pixels, and in addition thereto as encoded metadata at least one of the weights (wR, wG, wB, wY) usable in one of the above apparatus or method, which will typically be realized in that the signal is so defined that the receivers uniquely know what the weights mean, namely that they are intended to be used as weights for the respective color components prior to maximum calculation.
• the present invention embodiments can be realized in many technical variants, e.g. the image color processing apparatus (200) may be realized as, or comprised in an image or video encoder or decoder, as comprised in e.g. a settopbox, or display, or camera, etc.
• the image color processing apparatus (200) may be realized as, or comprised in an image or video encoder or decoder, as comprised in e.g. a settopbox, or display, or camera, etc.
• Fig. 1 schematically illustrates our method to encode at least two gradings of different luminance dynamic range, based on encoding and transmitting, typically via legacy video communication technology, the required information as a set of images of one of the gradings, and data to be able to reconstruct at a receiving side the functions to be used to color map the first set of images to a second set being the other grading;
• Fig. 2 schematically illustrates our basic brightness mapping technology for dynamic range conversion, as we published it in WO2014/056679;
• Fig. 3 schematically illustrates simpler variants of our present invention, in which at least some of the RGB color components are weighed with scale factors typically smaller than or equal to one before being input in the maximum calculation unit, and a luminance input may also be present;
• Fig. 4 schematically illustrates a more complex embodiments, in which other components are present for delivering additional input to the maximum calculation unit, such as units to non- linearly map the color components (401, 7), a unit to calculate an arbitrary linear or non-linear combination of the color components (404), and a color analysis unit to set the weights;
• Fig. 5 schematically illustrates how a selection of some maximum values leads, via the predetermined mapping function 205 by the grader, to multiplicative factors (a) for ultimately doing the color processing.
• Fig. 6 shows the same principle of the color transformation based on the maximal one determination of the input color components, but in a non-linear or gamma domain.
• Fig. 3 shows an example of how our present invention can be embodied.
• a luminance calculation unit (306) which calculates the luminance as al *R+a2*G+a3*B, with fixed constants al,a2,a3 depending on the color representation system, e.g. P3, Rec. 709, Rec. 2020, etc.
• color processing before and after our presently described unit, e.g.
• luminance multiplier 304 may be a luminance multiplier 304 comprised, even if it multiplies by 1.0, but if it always multiples by 1.0 that component may be missing (but the video signal may still explicitly contain four weights, in which case hardware without a luminance multiplier can still correctly process even when ignoring the luminance weight rather than to set the luminance multiplier with it).
• a maximum calculation unit (201) then calculates which one of the inputs is the highest, which we call M (e.g. the green component, having a value of 180*4, if the word length of the components is e.g. 10 bit). Then a brightness mapper (202) applies a function to M, which function has been previously designed by a grader to make sure that the resultant image has a good look.
• This image may be e.g. an LDR grading to be rendered on displays of PB around 100 nit, calculated from a master HDR grading.
• the master HDR images, and the data of the function may e.g.
• Fig. 4 shows what is possible in more complex embodiments.
• a color analysis unit (410) can calculate weights, whether they were already present and have to be overwritten at least for some situations, or have to be calculated on the fly (in the case that no weights are communicated, but one or more algorithms to derive them).
• any analysis of the color situation can be done, typically simply looking at the color of the pixel itself, but also other colors of the image may be evaluated, e.g. of surrounding pixels to estimate if noise would be conspicuous, and also depending on what is required, such as PB of the required grading, viewing surround conditions, acceptable quality in view of price of the content, etc.
• Non- linear function application units (401, 402, 403) may be present to provide non-linear color components (NR, NG, NB) as input to the maximum calculation unit. This is advantageous e.g. if one wants to design a mapping function 205 which is differently sampled, e.g. on a logarithmic axes system, etc.
• a non-linear transformation unit may also be present at the output of the maximum calculation unit (i.e. between units 201 and 202), i.e. non-linearly transforming the maximum M, whether it was selected from linear and or non-linear color components as input.
• a color component combination unit (404) may also be present. With this e.g. some other brightness estimate SBC can be calculated than the luminance, e.g. as
• bl *R+b2*G+b3*B It may also combine linearly or non- linearly the non- linear components NR,NG,NB, or in fact calculating whatever non-linear function yielding a single real- valued parameter over the cube of possible input colors (which function may typically be embodied as one or more LUTs, which may have been optimized e.g. for particular classes of content, like which camera captured the content and potentially under which conditions, e.g. night versus day, what type the content is, e.g. nature movie versus cartoon, or graphics or content containing some graphics, like maybe a tutorial or the news, etc.).
• an metadata encoder 450 will collect all the parameters, such as all the weights, parameters defining the shapes of the non-linear functions, or the calculations of parameters, or the data of LUTs, or the algorithms classifying particular colorimetric properties of the to be processed image(s), etc., and after formatting this in a pre-agreed format, send this to a communication technology 451, e.g. a server connected to the internet for later supply to end customers, or a direct link to a customer, etc.
• a communication technology 451 e.g. a server connected to the internet for later supply to end customers, or a direct link to a customer, etc.
• image-related technologies like e.g. video supply systems, image or video processing software, image analysis or re-processing systems, etc.
• Fig. 6 shows how the same principle can be applied in non-linear RGB representation, typically classical gamma R'G'B' versions, being approximately a square root of the linear light RGB colors, as e.g. prescribed by the opto-electronic transfer function (which defines the mapping between the linear color components, e.g. R, and the luma codes R', and vice versa via the EOTF), e.g. according to Rec. 709 (note that apart from color non- linearities the color gamut shape stays the same for the chose red, green and blue primaries).
• the opto-electronic transfer function which defines the mapping between the linear color components, e.g. R, and the luma codes R', and vice versa via the EOTF
• Rec. 709 note that apart from color non- linearities the color gamut shape stays the same for the chose red, green and blue primaries).
• Matrix calculator 601 converts this Y"CbCr representation of the pixel color(s) to a highly non- linear (almost logarithmic) R", G", B" representation.
• Non-linear function calculation unit 602 applies the fixed non-linear function to transform those components to the classical luma ones R'G'B', i.e. defined according to typically e.g. Rec. 709 function defined as :
• Y' power([CR*R' A gam+ CG*G' A gam+ CB*B' A gam]; 1/gam), in which gam equals e.g. 2.0, indicates the power operation, and CR, CG and CB are the known component weights for luminance calculations, which can uniquely be calculated colorimetrically if one knows the chromaticities of the RGB primaries and the white point. So in this manner one gets a realistic value of the pixel luma corresponding to its actual luminance.
• Maximum calculation unit 604 is again any of the weighed component maximum calculation embodiments our invention allows, and scale factor calculation unit 202203 comprises the transformation of the input brightness correlate V from the maximum to a scale factor for the multiplicative processing, i.e. comprises what units 202 and 203 do.
• multipliers 605, 606, and 607 realize via scale factor a the color transformation to the output color (Rs,GS,Bs), which is in this embodiment matrixed again to Y'CbCr by color matrixer 608, but this is now in the gamma domain, i.e. Y' code defined according to e.g. typically the Rec. 709 EOTF.
• the algorithmic components disclosed in this text may (entirely or in part) be realized in practice as hardware (e.g. parts of an application specific IC) or as software running on a special digital signal processor, or a generic processor, etc. They may be semi- automatic in a sense that at least some user input may be/have been (e.g. in factory, or consumer input, or other human input) present.
• all variants of a creation side like an encoder may be similar as or correspond to corresponding apparatuses at a consumption side of a decomposed system, e.g. a decoder and vice versa.
• Several components of the embodiments may be encoded as specific signal data in a signal for transmission, or further use such as
• Appendix in this application is used in its broadest sense, namely a group of means allowing the realization of a particular objective, and can hence e.g. be (a small part of) an IC, or a dedicated appliance (such as an appliance with a display), or part of a networked system, etc.
• Arrangement or “system” is also intended to be used in the broadest sense, so it may comprise inter alia a single physical, purchasable apparatus, a part of an apparatus, a collection of (parts of) cooperating apparatuses, etc.
• the computer program product denotation should be understood to encompass any physical realization of a collection of commands enabling a generic or special purpose processor, after a series of loading steps (which may include intermediate conversion steps, such as translation to an intermediate language, and a final processor language) to enter the commands into the processor, to execute any of the characteristic functions of an invention.
• the computer program product may be realized as data on a carrier such as e.g. a disk or tape, data present in a memory, data traveling via a network connection -wired or wireless- , or program code on paper.
• characteristic data required for the program may also be embodied as a computer program product. Such data may be (partially) supplied in any way.
• the invention or any data usable according to any philosophy of the present embodiments like video data may also be embodied as signals on data carriers, which may be removable memories like optical disks, flash memories, removable hard disks, portable devices writeable via wireless means, etc.

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• 2015
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  • 2015-10-22 RU RU2017128208A patent/RU2707728C2/ru active

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