TW201835861A - Tone curve mapping for high dynamic range images - Google Patents

Abstract

Methods for mapping an image from a first dynamic range to a second dynamic range are presented. The mapping is based on a function that includes two spline polynomials determined using three anchor points and three slopes. The first anchor point is determined using the black point levels of the input and target output, the second anchor point is determined using the white point levels of the input and target output, and the third anchor point is determined using mid-tones information data for the input and target output. The mid-tones level of the target output is computed adaptively based on an ideal one-to-one mapping and by preserving input contrast in both the blacks and the highlights. An example tone-mapping transfer function based on third order (cubic) Hermite splines is presented.

Description

Tone curve mapping for high dynamic range images

The present invention is generally directed to images. More specifically, an embodiment of the present invention relates to determining parameters for mapping high dynamic range (HDR) images and video signals from a first dynamic range to a tone curve of a second dynamic range.

As used herein, the term "dynamic range" (DR) may relate to a range of intensity (eg, illuminance, brightness) in an image with respect to the human visual system (HVS) (eg, from the darkest gray (black) to the brightest) White (highlight) one of the abilities. In this sense, DR is about a "scenes correlation" strength. The DR may also be capable of fully or approximately presenting a range of intensities of a particular extent to a display device. In this sense, DR is about a "display correlation" strength. Unless a particular meaning is explicitly stated as having a particular importance at any point in the description herein, it should be inferred that the term may be used interchangeably, in any sense. As used herein, the term high dynamic range (HDR) relates to the DR breadth of one of some 14 to 15 orders of magnitude across the human visual system (HVS). In fact, DR (humans can simultaneously perceive a wide breadth of the intensity range when DR is exceeded) can be slightly truncated relative to HDR. As used herein, the terms enhanced dynamic range (EDR) or visual dynamic range (VDR) may be independently or interchangeably related to DR, which may be perceived by a human visual system (HVS) within a scene or image, the HVS including The eye moves, allowing some of the light across the scene or image to adapt to changes. In practice, the image includes one or more color components (eg, luminance Y and chrominance Cb and Cr), wherein each color component is represented by one of n bits per pixel (eg, n =8). Using linear illumination encoding, images with n ≤ 8 (for example, color 24-bit JPEG images) are treated as images with a standard dynamic range, while images with n >8 can be viewed as images with enhanced dynamic range. EDR and HDR images can also be stored and distributed using high precision (eg, 16 bit) floating point formats such as the OpenEXR file format developed by Industrial Light and Magic. As used herein, the term "post-data" relates to any auxiliary information that is transmitted as part of a coded bitstream and that assists a decoder in presenting a decoded image. Subsequent settings may include, but are not limited to, color space or range information, reference display parameters, and auxiliary signal parameters as described herein. Most consumer desktop displays currently support illumination of 200 cd/m ² or nit to 300 cd/m ² or nit. Most consumer HDTVs range from 300 nits to 500 nits, with new models reaching 1000 nits (cd/m ² ). Such conventional displays are therefore typically low dynamic range (LDR) with respect to HDR or EDR, also referred to as a standard dynamic range (SDR). When the availability of EDR content continues to grow due to the development of both capture devices (eg, cameras) and EDR displays (eg, PRM-4200 professional benchmark monitors from Dolby Laboratories), EDR content can be tinted And displayed on EDR displays that support higher dynamic range (eg, from 1000 nits to 5000 nits or higher). In general and without limitation, the method of the present invention relates to any dynamic range above SDR. High dynamic range (HDR) content authoring is now very common as this technology provides more realistic and lifelike images than earlier formats. However, many display systems, including hundreds of millions of consumer television displays, are unable to reproduce HDR images. Moreover, due to the wide range of HDR displays (ie, from 1,000 nits to 5,000 nits or higher), HDR content optimized on an HDR display may not be suitable for direct playback on another HDR display. One method used to serve the entire market is to create multiple versions of new video content; that is, one version uses HDR images and the other version uses standard dynamic range (SDR) images. However, this requires content authors to author their video content in a variety of formats, and may require consumers to know which format to purchase for their particular display. A potentially better approach might be to create a version of the content (in HDR form) and use an image data transformation system (eg, as part of a video converter functionality) to automatically down convert the input HDR content ( Or upconverting) for proper output SDR or HDR content. As the inventors hereunder understand, in order to improve the existing display scheme, an improved technique for determining a tone curve for display mapping of HDR images has been developed. The methods described in this paragraph are methods that can be pursued, but are not necessarily methods that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the methods described in this paragraph are considered to be prior art only because they are included in this paragraph. Similarly, questions identified with respect to one or more methods should not be assumed to be recognized based on this paragraph in any prior art unless otherwise indicated.

CROSS-REFERENCE TO RELATED APPLICATIONS RELATED APPLICATIONS RELATED APPLICATIONS RELATED APPLICATIONS RELATED APPLICATIONS RELATED APPLICATIONS RELATED APPLICATIONS Priority No. 62/465,298, each of which is incorporated herein by reference. A method for determining a tone curve for mapping a high dynamic range (HDR) image is described herein. In the following description, numerous specific details are set forth However, it will be appreciated that the invention may be practiced without such specific details. In other instances, well-known structures and devices are not described in detail to avoid unnecessarily obscuring, obscuring or obscuring the invention. SUMMARY The exemplary embodiments described herein relate to methods for determining a tone curve for mapping a high dynamic range (HDR) image. In an embodiment, in an embodiment, for an input image, a processor receives the first information material, and includes one of the first dynamic range, the input black level (x1, SMin), and an input intermediate. Hue level (x2, SMid) and an input white point level (x3, SMax). The processor also accesses a second information material of an output image in a second dynamic range, the second information material including a first output black level (TminPQ) and a first output of the second dynamic range White point level (TmaxPQ). The processor determines one of the second dynamic ranges to output an intermediate tone value based on the first and the second information material. The processor calculates a second output black point and a second output white point in the second dynamic range based on the second information material and the output halftone value. Then, the processor calculates a tail slope, a head slope, and a midtone slope based on the first information material, the second information data, and the output halftone value. The processor determines a transfer function for mapping a pixel value of the input image in the first dynamic range to a corresponding pixel value of the output image in the second dynamic range, wherein the transfer function includes two a segment, wherein the first segment is determined based on the tail slope, the midtone slope, the input black point level, the input halftone level, the second output black point, and the output halftone value, and the The second stage is determined based on the midtone slope, the head slope, the input midtone level, the input white point level, the output halftone value, and the second output white point. The processor maps the input image to the output image using the determined transfer function. In one embodiment, the processor calculates the second output black point and the second output white point based on the first information material, the second information material, and the output halftone value. In one embodiment, the processor calculates a tail slope based on the input black point level, the input midtone level, the second output black point, and the output midtone value. In one embodiment, the processor calculates a head slope based on the input white point level, the input midtone level, the second output white point, and the output midtone value. In one embodiment, the processor calculates a midtone slope based on the first information material, the second output black point, the second output white point, and the output midtone value. Video Coding of Dynamic Range Converted HDR Signals FIG. 1 depicts an exemplary procedure for displaying a conventional video delivery pipeline (100) from various stages of video capture to video content display. A video frame sequence (102) is captured or generated using the image generation block (105). The video frame (102) can be generated (e.g., by a digital camera) digitally or by a computer (e.g., using computer animation) to provide video material (107). Alternatively, the video frame (102) can be captured on the film by a movie camera. The film is converted to a digital format to provide video material (107). In a production phase (110), the video material (107) is edited to provide a video production stream (112). The video material of the production stream (112) is then provided at block (115) to a processor for post-production editing. Block (115) post-production editing may include adjusting or modifying the color or brightness in a particular region of an image based on the creative intent of the video creator to enhance image quality or achieve a particular appearance of the image. This is sometimes referred to as "color timing" or "color grading." Other edits (e.g., scene selection and sorting, image cropping, adding computer generated visual special effects, etc.) may be performed at block (115) to produce a final version (117) for distribution. During the post-production editing (115), the video image is viewed on a reference display (125). After post-production (115), the video material of the final production (117) can be passed to a coding block (120) for downstream transmission to a decoding and playback device, such as a television, video converter, movie theater, and the like. In some embodiments, the encoding block (120) can include an audio and video encoder, such as an encoder defined by ATSC, DVB, DVD, Blu-Ray, and other transfer formats to produce an encoded bitstream (122). . In a receiver, the decoding unit (130) decodes the encoded bitstream (122) to produce a decoded signal (132) that is identical or strictly approximated by one of the representation signals (117). The receiver can be attached to a target display (140), which can have completely different characteristics than the reference display (125). In this case, a display management block (135) can be used to map the dynamic range of the decoded signal (132) to the characteristics of the target display (140) by generating a display mapping signal (137). The use of a Sigmoid mapping for image transformation is disclosed in U.S. Patent No. 8,593,480, entitled " Method and Apparatus for image data transformation ", which is hereby incorporated by reference. Herein, the inventors have proposed an image transformation map using a parametric sigmoid function that can be uniquely determined using three anchor points and a midtone free parameter. An example of this function is depicted in Figure 2. As depicted in Figure 2, the mapping function (220) is defined by three anchor points (205, 210, 215): black point (x1, y1), midtone point (x2, y2), and white point (x3, y3). . This transformation has the following properties: • Values from x1 to x3 represent the range of possible values that describe the pixels that make up the input image. The value can be the brightness level of a particular color primary color (R, G, or B), which can be the overall illumination level of the pixel (ie, the Y component in a YCbCr representation). Typically, such values correspond to the darkest (blackpoint) and brightest (whitepoint) levels supported by the display used to author the content ("primary display"(125)); however, in some embodiments, When the characteristics of the reference display are unknown, the values may represent the minimum and maximum values in the input image (for example, the minimum and maximum values of R, G or B, illuminance, etc.), and the maximum and minimum values may be The data is received via the image or calculated in the receiver. • The value from y1 to y3 represents the range of possible values describing the pixels that make up the output image (again, the color primary color brightness or the overall illumination level). Typically, these values correspond to the darkest (blackpoint) and brightest (whitepoint) levels supported by the intended output display ("Target Display" (140)). Any input pixel having the value x1 is constrained to be mapped to one of the output pixels having the value y1, and any input pixel having the value x3 is constrained to be mapped to one of the output pixels having the value y3. • The values of x2 and y2 represent a specific mapping from input to output that is used as an anchor point for one of the "middle range" (or midtone) elements of the image. A considerable range is allowed in the particular choice of x2 and y2, and the '480 patent teaches many alternatives for how these parameters can be selected. Once these three anchor points are selected, the transfer function (220) can be described as (1) where C ₁ , C ₂ and C ₃ are constants, x indicates the input value of a color channel or illuminance, y indicates the corresponding output value, and n is a free parameter that can be used to adjust the midtone contrast. As described in the '480 patent, the C ₁ , C ₂ and C ₃ values can be determined by solving the following equation (2) The tone curve of equation (1) has been successfully applied to a variety of display mapping applications; however, as the inventors have appreciated, it also has a number of potential limitations, including: • Difficult to define tone curve parameters such that a specific range of target displays Remember that there is a one-to-one mapping in the memory. It is difficult to determine the parameters (ie, the exponent n ) to control the contrast. Subtle changes in the intermediate anchor point (x2, y2) may produce unexpected behavior. Do not allow the black anchor point (205) below and / Or a linear map above the white anchor point (215). Figure 3 depicts an example of a new tone mapping curve in accordance with one of the embodiments. As depicted in Figure 3, the tone mapping curve (320) includes up to four segments: • For values below (x1, y1) (x1 can also be negative), select line segment L1 · Spline S1, from (x1 , y1) to (x2, y2) · Spline S2, from (x2, y2) to (x3, y3) · For values greater than (x3, y3) (x1 can also be greater than 1), select line segment L2 in one In the embodiment and without limitation, a third-order (three-time) Hermitian polynomial is used to determine segments S1 and S2. As will be discussed later, the mapping using line segments L1 and L2 may be particularly useful when calculating the inverse of the tone curve, for example during inverse tone mapping (ie, when a high dynamic range image is required to be generated from a standard dynamic range image). of. As in equation (1), the curve (320) is controlled by three anchor points (305, 310, 315): black point (x1, y1), midtone value point (x2, y2), and white point (x3, y3) ). Furthermore, at each end point, each of the spline segments can be further constrained by two slopes; therefore the complete curve is controlled by three anchor points and three slopes: the slope of the tail at (x1, y1), (x2, y2 The midtone slope at the base and the slope of the head at (x3, y3). For example, considering that the same strip between the point (x1, y1) and the point (x2, y2) has a slope s1 at (x1, y1) and a slope s2 at (x2, y2), for an input x , the transfer function of the three Hermitian splines can be defined as: ), (3a) where ). (3b) In an embodiment, to ensure that there is no overshoot or undershoot (ie, to ensure that the curve is monotonic), the following rules can also be applied to the slopes s1 and s2: among them Mark a constant (for example, =3). In view of the Hermitian spline of equation (3), in one embodiment and without limitation, for a video input, ie, a perceptual quantizer (PQ) is used (eg, according to SMPTE ST 2084:2014, "High Dynamic Range EOTF of Mastering Reference Displays") encodes one of the video inputs and defines a complete curve based on the following parameters: • SMin=x1; indicates the minimum illumination of the source content. If not given, SMin can be set to represent one of the typical black values (eg, SMin = 0.0151) · SMax = x3; the maximum illumination of the source content is indicated. If not given, SMax can be set to indicate a large value of "highlight" (for example, SMax = 0.9026) · SMid = x2; the average (eg, arithmetic, median, geometric) illumination of the source content is indicated. In some embodiments, it may simply indicate one of the "important" illuminance features in the input picture. In some other embodiments, it may also indicate the average or median of a selected area (ie, a face). The SMid can be defined manually or automatically, and its value can be offset based on preferences to preserve a certain appearance in highlights or shadows. If not given, the SMid can be set to a typical average (for example, SMid = 0.36, representing skin tone). Such data may be received using image or source post-data, which may be calculated by a display management unit (e.g., 135), or the like, based on known assumptions regarding the primary or reference display environment. In addition, it is assumed that the target display knows the following information (for example, by reading the extended display identification data (EDID) of the display) to receive the following information: • TminPQ = minimum illumination of the target display • TmaxPQ = maximum illumination of the target display The term "PQ" as used herein indicates that this value (usually given in nits) is converted to a PQ value according to SMPTE ST 2084. To fully determine the mapping curve, the following points and parameters need to be calculated: TMin=y1; TMax=y3; TMid=y2; slopeMin=(x1,y1) slope; slopeMid=(x2,y2) slope; and slopeMax= The slope at (x3, y3). 4A depicts an exemplary procedure for determining an anchor point and a slope of a tone mapping curve, in accordance with an embodiment. In view of the input parameters (405) SMin, SMid, SMax, TminPQ, and TmaxPQ, step 412 calculates y2 (TMid). For example, in one embodiment, as long as the TMid is within the boundary points TminPQ and TmaxPQ and a predetermined buffer, the midtone anchor (SMid, TMid) may be selected to be on the 1-to-1 mapping line, ie, forcing TMid=SMid. For TMid values close to TminPQ and TmaxPQ, TMid can be selected to be within a fixed distance (eg, between TninPQ+ c and TmaxPQ- d , where c and d are fixed values) or a percentage of this value is calculated One of the distances. For example, TMid may be forced to never be lower than TminPQ+ *TminPQ or higher than TmaxPQ- b *TMaxPQ, where And a constant in the b system [0, 1], indicating a percentage value (for example, = b = 5% = 0.05). In view of TMid, step 425 calculates the remaining unknown parameters (eg, y1, y2, and three slopes). Finally, step 430 calculates two spline segments and two segment segments. In another embodiment, by attempting to maintain the input "tail contrast" (ie, the contrast between black (SMin) and midtone (SMid)) and input "head contrast" (ie, midtone (SMid) The original ratio between the contrast with the highlight (SMax) is further refined to calculate the TMid. An example of such a procedure according to an embodiment is depicted in FIG. 4B and also in pseudo-code in Table 1. The goal of the program is: • Determine that the output midtone anchor (SMid, TMid) is mapped as close as possible to the diagonal (1 to 1). That is, in the ideal case, the TMid should be as close as possible to the SMid to maintain the input midtone; If a one-to-one mapping is not possible, the TMid is determined such that the output values of the "tail contrast" and "head contrast" ranges are within predetermined limits of the corresponding input range. As used herein, the input "head contrast" is based on one of the functions (SMax-SMid), and the input "tail contrast" is based on one of the functions (SMid-SMin). Given the intermediate anchor point (x2, y2) or (SMid, TMid), determining the three slopes makes it possible to characterize the entire tone curve. Table 1 : Exemplary procedures for determining tone curve parameters In step 4 above, to calculate the head and tail offset parameters, the items are multiplied by an item labeled "offsetScalar," which in one embodiment can be expressed as This function is intended to provide a smooth transition between the maximum possible offset (eg, headroom*preservationHead or tailroom*preserveTail) and the corresponding head or tail slope. The s() function in equation (5) can be any suitable linear or non-linear function of |2*midLoc-1|. For example, in another embodiment: . (6) In the above step 8, the slopeMid is calculated to be close to the diagonal of a 1-to-1 mapping. In contrast, slopeMax is calculated as Proportionally maintain high brightness; that is, the slope between (x2, y2) and (x3, y3), and slopeMin is calculated as The ratio is kept black, that is, the slope between (x1, y1) and (x2, y2). The index h and t determine the speed at which the highlight or grayscale needs to "crash". Typical values for h and t include 1/2 or 4. In an embodiment, h = t . Given the three anchor points and three slopes, four segments can be generated as follows: if( < x ) //S1 curve ), (7a) where ). (7b) if( < x ) // S2 curve ), (7c) where ). (7d) if( x ) // L1 segment (7e) if( // L2 segment (7f) Returning to FIG. 4B, in view of the input parameters (405) (eg, SMin, SMid, SMax, TminPQ, and TmaxPQ), step (410) calculates a first target midtone value and associated target header based on the input parameters. Space and tail space values (see, for example, step 2 in Table 1). In view of the head and tail contrast preservation percentage (eg, about 50%), the first target halftone value, and the associated target headspace and tail space, step (415) calculates the head and tail offset (see, for example, the table). Step 4) in 1. Step (420) applies a head and tail offset to the input SMid value to calculate the target TMid value (see, for example, step 5 in Table 1). Next, step (425) calculates TMax and TMin based on the input parameters and TMid (see, for example, step 6 in Table 1). While attempting to maintain monotonicity, step (425) also calculates the two end slopes and the intermediate slope of the two splines (see, for example, step 8 in Table 1). In view of the input parameters TMid, TMin, TMax and the three slopes, the tone mapping curve can then be calculated in step (430) using equation (7). Figure 5 depicts two different examples of the proposed tone curve, mapping PQ encoded data from a first dynamic range to a second lower dynamic range. Note that the same curve can also be used for an inverse mapping, ie for translating data from a lower dynamic range back to the original high dynamic range. In an embodiment, the inverse mapping can be calculated as follows: • As described earlier, the tone mapping curve is derived, ie, expressed as y=f(x) · Generate a forward lookup table, using y _i = f ( x _i ) The input x _i value is mapped to the output y _i value. A reverse lookup table is generated, using the value from the forward LUT (ie, If ,then = ) will enter a low dynamic range value Map to output higher dynamic range values , • Generate additional values for the inverse LUT by interpolating the existing values. For example, if By versus Interpolate between them to produce a corresponding output . 6A depicts how the input midtone value (SMid) is mapped to the output midtone value (TMid) to determine the midtone of the tone curve mapping function (eg, using steps 1 through 4 in Table 1), according to an embodiment. Anchor point. Given that SMin = 0.01, SMax = 0.92, and TminPQ = 0.1, curve 605 depicts how SMid maps to TMid when TmaxPQ = 0.5, and curve 610 depicts how SMid maps to TMid when TmaxPQ = 0.7. As can be seen from Figure 6A, it is observed that the function 605 is not monotonic within a small range of SMid values, i.e., unexpected results may occur during asymptotic or fading. To solve this problem, in step 4 of Table 1, the following pseudo-code can be used to calculate the head and tail offset: cutoff = a; / / for example, a = 0.5. offsetHead=min(max(0,(midLoc-cutoff))*TDR,max(0,headroom*preservationHead+midLoc_1)*TDR); offsetTail=min(max(0,(cutoff-midLoc))*TDR, max( 0,tailroom*preserveTail-midLoc)*TDR); where cutoff is a variable that preferentially maintains highlights and shadows by specifying the percentage of the target dynamic range that the head and tail offsets will be clipped. For example, a cutoff value of 0.5 gives a priority order in which highlights and shadows are equal, and a cutoff value of 0.7 gives a higher priority to highlights than shadows. This method is computationally simpler because it does not require the calculation of a cosine function or a square root function, and it remains monotonic as depicted in Figure 6B. Given that SMin = 0.01, SMax = 0.92, and TminPQ = 0.1, in Figure 6B, curve 615 depicts how SMid maps to TMid when TmaxPQ = 0.5, and curve 620 depicts how SMid maps to TMid when TmaxPQ = 0.7. Compared to equation (1), the proposed tone curve exhibits several advantages, including: • Using the slopeMid parameter, a one-to-one mapping between the SMid value and the TMid value within a specific range of the target display can be defined to maintain Contrast; · Image contrast can be explicitly controlled via the slopeMid and contrastFactor variables (see Table 1, Step 8). For example, in one embodiment, the range of the contrastFactor value may not be limited to between 0.5 and 2.0, where the preset value is contrastFactor=1; • around the midtone anchor point (x2) by dividing the entire curve into two splines. , y2) No more unexpected behavior; • Use SlopeMin and SlopMax to pre-define the behavior of the mapping curve before the black anchor and after the white anchor; • The curve can map negative input values (for example, . This condition may occur due to noise or other system conditions (eg, spatial filtering). The negative value is usually clamped to 0; however, this clamp may eventually increase noise and reduce overall quality. These clamp-based artifacts can be reduced or eliminated by being able to map negative input values. · Tone mapping curves can be easily reversed by simple switching from x to y mapping or one y to x mapping; • No non-integer exponents or power functions are required, so calculations are faster and more efficient. Because no non-integer index is used. Regarding the last point, for a computational point of view, for a non-trivial contrast value (for example, And/or when n is not an integer) the function parameters in equation (2) need to use six power functions (for example, for y=pow(x,n) ). In contrast, the calculations in Table 1 never require any non-integer power functions (calculating a power of 2 or 4 requires a simple multiplication). In summary, Equation (7) requires several multiply/divide and add/subtract operations for each input sample compared to equation (1), but does not require a power function. In some embodiments, equation (7) can be implemented using a look-up table. More importantly, user research performed by the inventor seems to indicate that the user prefers the overall image quality of the image produced using the new tone mapping function (320). Illustrative Computer System Embodiments Embodiments of the present invention may be implemented in a computer system, a system configured in an electronic circuit and components, such as an integrated circuit (IC) device of a microcontroller, a field programmable gate array ( FPGA) or another configurable or programmable logic device (PLD), a discrete time or digital signal processor (DSP), an application specific IC (ASIC), and/or one of such systems, devices or components Or more equipment to implement. The computer and/or IC can execute, control or execute instructions related to image transformation for images having a high dynamic range, such as the instructions described herein. The computer and/or IC can calculate any of a variety of parameters or values associated with the image transformation procedures described herein. Image and video embodiments can be implemented in hardware, software, firmware, and various combinations thereof. Certain embodiments of the present invention include a computer processor that executes a software instruction that causes a processor to perform one of the methods of the present invention. For example, as described above, one or more processors in a display, an encoder, a video converter, a transcoder, etc., by executing software instructions in a program memory accessible by the processor A method related to image conversion of HDR images can be implemented. The invention may also be provided in the form of a program product. The program product can include any non-transitory media carrying a collection of computer readable signals including instructions that, when executed by a data processor, cause the data processor to perform one of the methods of the present invention. The program product according to the present invention can be in any of a variety of forms. The program product may include, for example, physical media, such as a magnetic data storage medium containing a floppy disk, a hard disk drive, an optical data storage medium including a CD ROM, a DVD, and an electronic material storage medium including a ROM, a flash memory RAM, and the like. The computer readable signal on the program product may be compressed or encrypted as appropriate. In the case of a component (eg, a software module, processor, assembly, device, circuit, etc.) as mentioned above, unless otherwise indicated, a reference to the component (including one of the "devices" References to the equivalents of the components, such as any components that perform the functions of the described components (e.g., functionally equivalent components), are not structurally equivalent to the practice of the present invention. The components of the disclosed structure are illustrated to illustrate the functions of the illustrative embodiments. Equivalents, extensions, alternatives, and miscellaneous thus describe an illustrative embodiment of efficient image conversion from HDR video to SDR video. In the foregoing specification, embodiments of the invention have been described with reference Therefore, the sole and exclusive indications of the invention and the applicant's intention to be the sole and exclusive indication of the invention are the scope of the application for the application of this application, which is in the form of Subsequent correction). Any definitions expressly set forth herein for terms contained in such claims will determine the meaning of such terms used in the claim. Therefore, the limitations, elements, properties, characteristics, advantages or attributes not specifically recited in the claims should not limit the scope of the claim in any way. Accordingly, the specification and drawings are to be regarded as a Various aspects of the present invention can be understood from the following enumerated exemplary embodiments (EEE): EEE 1. A method for mapping an image from a first dynamic range to a second dynamic range using a processor, The method includes: accessing, in the first dynamic range, the first information material of an input image, including one of the first dynamic range, an input black level (x1, SMin), and an input intermediate tone level (x2, SMid) and an input white point level (x3, SMax); accessing the second information material of the output image in the second dynamic range, the second information material comprising one of the second dynamic range and the first output a black point level (TminPQ) and a first output white point level (TmaxPQ); determining one of the second dynamic range output midtone values based on the first information material and the second information material; And the output intermediate tone value is used to calculate a second output black point and a second output white point in the second dynamic range; based on the first information material, the second information material, and the output intermediate tone value To calculate a tail slope, a head slope And a midtone slope; determining a transfer function for mapping a pixel value of the input image in the first dynamic range to a corresponding pixel value of the output image in the second dynamic range, wherein the transfer The function includes two segments, wherein the first segment is determined based on the tail slope, the midtone slope, the input black point, the input midtone level, the second output black point, and the output halftone value, and the The second stage is determined based on the midtone slope, the head slope, the input midtone level, the input white point, the output halftone value, and the second output white point; and using the determined transfer function The input image is mapped to the output image. EEE2. The method of EEE 1, wherein the first dynamic range comprises a high dynamic range and the second dynamic range comprises a standard dynamic range. EEE3. The method of EEE 1 or EEE 2, wherein the transfer function further comprises a first line segment for an input value lower than the input black point in the first dynamic range, wherein the line segment Has a slope equal to one of the tail slopes. EEE 4 The method of EEE 3, wherein the transfer function of the first line segment comprises Where x indicates an input pixel value, y indicates an output pixel value, slopeMin indicates the tail slope, TMin indicates the second output black point in the second dynamic range, and SMin indicates the input in the first dynamic range Black spots. The method of any one of EEE 1 to 4, wherein the transfer function further comprises a second line segment for inputting an input value greater than the input white point in the first dynamic range, wherein the line segment Has a slope equal to one of the slopes of the head. EEE 6. The method of EEE 5, wherein the transfer function of the second line segment comprises Where x indicates an input pixel value, y indicates an output pixel value, slopeMax indicates the head slope, TMax indicates the second output white point in the second dynamic range, and SMax indicates the first dynamic range Enter a white point. The method of any of EEE 1 to 6, wherein the first segment and/or the second segment is determined based on a third-order Hermitian spline polynomial. EEE 8. The method of EEE 7, wherein determining the first segment comprises calculating ), among them x indicates an input pixel value, y indicates an output pixel value, slopeMin indicates the tail slope, slopeMid indicates the midtone slope, TMin and TMid indicate the second output black point and the output halftone level, and SMin and The SMid indicates the input black point in the first dynamic range and the input midtone level. EEE 9. The method of EEE 7 or EEE 8, wherein the second segment is determined to include calculations ), (5c) where x indicates an input pixel value, y indicates an output pixel value, slopeMax indicates the head slope, slopeMid indicates the midtone slope, TMid and TMax indicate the output halftone level in the second dynamic range and the first Two output white points, and SMid and SMax indicate the input halftone level and the input white point in the first dynamic range. EEE 10. The method of any of EEE 1 to 9, wherein calculating the output midtone value comprises calculating: if SMid TminPQ+ *TMinPQ then TMid = TMinPQ+ *TMinPQ; otherwise if SMid > TmaxPQ- b *TmaxPQ then TMid = TmaxPQ- b *TmaxPQ; otherwise TMid = SMid; where TMid indicates the output midtone value, And the percentage value in b system [0, 1], SMid indicates the input halftone level, and TminPQ and TmaxPQ include the value in the second information material. The method of any one of EEE 1 to 9, wherein calculating the output midtone value further comprises: determining a preliminary output of the second dynamic range based on the first information material and the first output black point a midtone value and first and second boundary values of the preliminary output halftone value; calculating the second based on the preliminary output halftone value, the first and second boundary values, and one or more input contrast saved values a head offset and a tail offset in the dynamic range; and calculating the output in the second dynamic range based on the input midtone level in the first dynamic range and the head and tail offsets Midtone value. EEE12. The method of EEE 11, wherein determining the preliminary output midtone value and the first and second boundary values of the first output midtone value comprises calculating midLoc=(SMid-TminPQ)/TDR; headroom=(SMax -SMid)/TDR; tailroom=(SMid-SMin)/TDR; where TDR = TmaxPQ-TminPQ, midLoc indicates the initial output midtone value, and tailroom and headroom indicate the first and second of the first output midtone value The second boundary value, SMin, SMid, and SMax, indicates the first information material, and TminPQ indicates the first output black point level. EEE 13. The method of EEE 11 or EEE 12, wherein at least one of the contrast preservation values is approximately 50%. The method of any one of EEE 11 to 13, wherein calculating the output midtone value (TMid) comprises calculating TMid = SMid-offsetHead + offsetTail, wherein SMid indicates the input midtone bit in the first dynamic range Quasi, and offsetHead and offsetTail indicate the head and tail offsets. EEE 15. The method of EEE 14, wherein calculating the second output white point and the second output black point in the second dynamic range comprises calculating TMax = min(TMid+SMax-SMid, TmaxPQ), TMin = max( TMid-SMid+SMin, TminPQ, where TMin indicates the second output black point, TMax indicates the second output white point, and SMin and SMax indicate the input black point and the input white point in the first dynamic range, TminPQ and TmaxPQ indicates the first output black point and the first output white point in the second dynamic range. EEE 16. The method of EEE 10 or EEE 15, further comprising maximizing one of the tail slopes (maxMinSlope) and / or one of the head slope maxima (maxMaxSlope) is calculated as maxMinSlope = 3*(TMid-TMin)/(SMid-SMin), maxMaxSlope=3*(TMax-TMid)/(SMax-SMid). The method of EEE 16, wherein calculating the tail slope (slopeMin), the midtone slope (slopeMid), and the head slope (slopeMax) further comprises calculating slopeMin = min([maxMinSlope,(( TMid - TMin)/(SMid - SMin)) ² ]); slopeMax = min([maxMaxSlope,1,((TMax - TMid)/(SMax - SMid)) ⁴ ]); slopeMid=min([maxMinSl Ope, maxMaxSlope, contrastFactor*(1-SMid+TMid)]); wherein the contrastFactor indicates a contrast parameter. EEE 18. The method of any of EEE 1 to 17, further comprising determining a reverse lookup table to Mapping the image from the second dynamic range back to the first dynamic range, the method comprising: determining a forward lookup table based on the determined transfer function, the forward lookup table having a plurality of x in the first dynamic range ( i) mapping the value to the y(i) value in the second dynamic range; and generating the reverse lookup table by setting the following: the reverse lookup table for the plurality of y 's in the second dynamic range ( k) the value is mapped to the corresponding x'(k) value in the first dynamic range: if y' ( k ) = y ( i ), then x' ( k ) = x ( i ) otherwise if y ( i ) <y' ( k ) < y ( i +1), the corresponding output x'(k) is generated by interpolating a value between x(i) and x(i + 1 ). EEE 19. An apparatus comprising a processor and configured to perform any of the methods as described in EEE 1 through 18. EEE 20. A non-transitory computer readable storage medium having stored thereon computer executable instructions for performing the method of any one of EEEs 1 to 18 in one or more processors.

100‧‧‧Video transmission pipeline

102‧‧‧Video frame sequence

105‧‧‧Video frame sequence

107‧‧‧Video Information

110‧‧‧Production stage

112‧‧‧Video production stream

115‧‧‧ post-production editor

117‧‧‧ final production

120‧‧‧ coding block

122‧‧‧ encoded bit stream

125‧‧‧Reference display

130‧‧‧Decoding unit

132‧‧‧Decoding signal

135‧‧‧Display Management Block

137‧‧‧Display map signal

140‧‧‧Target display

205‧‧‧ anchor

210‧‧‧ Anchor

215‧‧‧ Anchor

220‧‧‧transfer function

305‧‧‧ Anchor

310‧‧‧ Anchor

315‧‧‧ Anchor

320‧‧‧ overall image quality

405‧‧‧ square

410‧‧‧ square

412‧‧‧ square

415‧‧‧ square

420‧‧‧ square

425‧‧‧ square

430‧‧‧ square

605‧‧‧ Curve

610‧‧‧ Curve

615‧‧‧ Curve

620‧‧‧ Curve

L1‧‧‧ line segment

L2‧‧‧ line segment

S1‧‧‧ Spline/Curve

S2‧‧‧ Spline/Curve

An embodiment of the present invention is illustrated by way of example in the accompanying drawings, and FIG. Figure 2 depicts an exemplary mapping function for mapping an image from a first dynamic range to a second dynamic range using three anchor points in accordance with the prior art; Figure 3 depicts an embodiment in accordance with an embodiment of the present invention An exemplary mapping function for mapping an image from a first dynamic range to a second dynamic range; FIGS. 4A and 4B depict exemplary procedures for determining a tone mapping function, in accordance with an embodiment of the present invention; Figure 5 (a) and (b) depict two exemplary mapping functions determined in accordance with an embodiment of the present invention; and Figures 6A and 6B depict how the input midtone values are mapped in accordance with an embodiment of the present invention. An exemplary graph to the midtone value of the one tone curve mapping function is output to the midtone value.

Claims (19)

A method for mapping an image from a first dynamic range to a second dynamic range using a processor, the method comprising: accessing, by the first dynamic range, a first information material of an input image, the first An information material includes one of the first dynamic range input black level (x1, SMin), an input intermediate tone level (x2, SMid), and an input white point level (x3, SMax); And accessing, by the second dynamic range, the second information material of the output image, the second information material comprising one of the first output black point level (TminPQ) and a first output white point level (TmaxPQ) of the second dynamic range Determining one of the second dynamic ranges based on the first information data and the second information data to output an intermediate tone value; calculating the second dynamic range based on the second information material and the output intermediate tone value a second output black point and a second output white point; calculating a tail slope, a head slope, and a midtone slope based on the first information material, the second information data, and the output halftone value; Transfer function The number is used to map a pixel value of the input image in the first dynamic range to a corresponding pixel value of the output image in the second dynamic range, where the transfer function includes two segments, wherein the first segment is based on the Determining the tail slope, the midtone slope, the input black point level, the input halftone level, the second output black point, and the output halftone value, and the second segment is based on the midtone slope, the Determining a head slope, the input midtone level, the input white point level, the output halftone value, and the second output white point; and mapping the input image to the output image using the determined transfer function. The method of claim 1, wherein calculating the second output black point and the second output white point in the second dynamic range are further based on the first information material. The method of claim 1 or 2, wherein: calculating the tail slope is based on the input black point level, the input midtone level, the second output black point, and the output midtone value; calculating the head slope system Based on the input white point level, the input midtone level, the second output white point, and the output halftone value; and calculating the midtone slope based on the first information material, the second output black point, the The second output white point and the output halftone value. The method of claim 1 or 2, wherein the first dynamic range comprises a high dynamic range and the second dynamic range comprises a standard dynamic range. The method of claim 1 or 2, wherein the transfer function further comprises a first line segment for an input value lower than the input black point level in the first dynamic range, wherein the line segment Having a slope equal to one of the slopes of the tail, wherein the transfer function for the first line segment as appropriate includes Where x indicates an input pixel value, y indicates an output pixel value, slopeMin indicates the tail slope, TMin indicates the second output black point in the second dynamic range, and SMin indicates the input in the first dynamic range Black spots are standard. The method of claim 1 or 2, wherein the transfer function further comprises a second line segment for an input value greater than the input white point level in the first dynamic range, wherein the line segment has equal to the a slope of the slope of the head, wherein the transfer function for the second line segment as appropriate includes Where x indicates an input pixel value, y indicates an output pixel value, slopeMax indicates the head slope, TMax indicates the second output white point in the second dynamic range, and SMax indicates the first dynamic range Enter the white point level. The method of claim 1 or 2, wherein the first segment and/or the second segment is determined based on a third-order Hermitian spline polynomial. The method of claim 7, wherein the determining the first segment comprises calculating ), among them x indicates an input pixel value, y indicates an output pixel value, slopeMin indicates the tail slope, slopeMid indicates the midtone slope, TMin and TMid indicate the second output black point and the output halftone value, and SMin and SMid The input black point level and the input halftone level in the first dynamic range are indicated. The method of claim 7, wherein the determining the second segment comprises calculating ), (5c) where x indicates an input pixel value, y indicates an output pixel value, slopeMax indicates the head slope, slopeMid indicates the midtone slope, TMid and TMax indicate the output halftone value in the second dynamic range, and the second The white point is output, and SMid and SMax indicate the input halftone level and the input white point level in the first dynamic range. The method of claim 1 or 2, wherein calculating the output midtone value comprises calculating: if SMid TminPQ+ *TMinPQ then TMid = TMinPQ+ *TMinPQ; otherwise if SMid > TmaxPQ- b *TmaxPQ then TMid = TmaxPQ- b *TmaxPQ; otherwise TMid = SMid; where TMid indicates the output midtone value, And the percentage value in b system [0, 1], SMid indicates the input halftone level, and TminPQ and TmaxPQ include the value in the second information material. The method of claim 1 or 2, wherein calculating the output halftone value further comprises: determining, based on the first information material and the first output black point, a preliminary output intermediate tone value and the preliminary Outputting first and second boundary values of the midtone value; calculating one of the second dynamic ranges based on the preliminary output halftone value, the first and second boundary values, and one or more input contrast retention values a portion offset and a tail offset; and calculating the output halftone value in the second dynamic range based on the input midtone level in the first dynamic range and the head and tail offsets. The method of claim 11, wherein determining the preliminary output midtone value and the first and second boundary values of the first output midtone value comprises calculating midLoc = (SMid - TminPQ) / TDR; headroom = (SMax - SMid)/TDR; tailroom = (SMid-SMin)/TDR; where TDR = TmaxPQ-TminPQ, midLoc indicates the preliminary output midtone value, and tailroom and headroom indicate the first and second of the first output midtone value The boundary value, SMin, SMid, and SMax indicate the first information material, and TminPQ indicates the first output black point level. The method of claim 11, wherein the at least one contrast retention value is approximately 50%. The method of claim 11, wherein calculating the output halftone value (TMid) comprises calculating TMid = SMid-offsetHead + offsetTail, wherein SMid indicates the input midtone level in the first dynamic range, and offsetHead and offsetTail indicate the Wait for the head and tail offset. The method of claim 14, wherein calculating the second output white point and the second output black point in the second dynamic range comprises calculating TMax = min(TMid+SMax-SMid, TmaxPQ), TMin = max(TMid- SMid+SMin, TminPQ, where TMin indicates the second output black point, TMax indicates the second output white point, and SMin and SMax indicate the input black point level and the input white point level in the first dynamic range. And TminPQ and TmaxPQ indicate the first output black point and the first output white point in the second dynamic range. The method of claim 10, further comprising calculating the maximum value of the tail slope (maxMinSlope) and/or the maximum value of the head slope (maxMaxSlope) as maxMinSlope = 3*(TMid-TMin)/(SMid- SMin), maxMaxSlope = 3*(TMax-TMid)/(SMax-SMid), wherein depending on the case: calculating the tail slope (slopeMin), the midtone slope (slopeMid), and the head slope (slopeMax) further includes calculating a slopeMin = min([maxMinSlope,((TMid-TMin)/(SMid-SMin)) ² ]); slopeMax=min([maxMaxSlope,1,((TMax-TMid)/(SMax-SMid)) ⁴ ]); slopeMid = min([maxMinSlope, maxMaxSlope, contrastFactor*(1-SMid+TMid)]); where the contrastFactor indicates a contrast parameter. The method of claim 1 or 2, further comprising determining a reverse lookup table to map an image from the second dynamic range back to the first dynamic range, the method comprising: determining a positive based on the determined transfer function a lookup table that maps a plurality of x(i) values in the first dynamic range to y(i) values in the second dynamic range; and generates the reverse by setting the following a lookup table that maps a plurality of y'(k) values in the second dynamic range to corresponding x'(k) values in the first dynamic range: if y' ( k ) = y ( i ), then x' ( k ) = x ( i ) otherwise if y ( i ) <y' ( k ) < y ( i +1), by interpolating a value at x(i) and x( The corresponding output x'(k) is generated between i + 1 ) . An apparatus comprising a processor and configured to perform the method of any one of claims 1 to 17. A non-transitory computer readable storage medium having stored thereon computer executable instructions for performing the method of any one of claims 1 to 17 in one or more processors.