WO2011002505A1 - Zone-based tone mapping - Google Patents
Zone-based tone mapping Download PDFInfo
- Publication number
- WO2011002505A1 WO2011002505A1 PCT/US2010/001863 US2010001863W WO2011002505A1 WO 2011002505 A1 WO2011002505 A1 WO 2011002505A1 US 2010001863 W US2010001863 W US 2010001863W WO 2011002505 A1 WO2011002505 A1 WO 2011002505A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- dynamic range
- image
- tone mapping
- high dynamic
- regions
- Prior art date
Links
- 238000013507 mapping Methods 0.000 title claims abstract description 51
- 238000000034 method Methods 0.000 claims abstract description 66
- 239000011159 matrix material Substances 0.000 claims abstract description 10
- 238000012805 post-processing Methods 0.000 claims description 3
- 230000008569 process Effects 0.000 description 16
- 230000011218 segmentation Effects 0.000 description 12
- 238000012545 processing Methods 0.000 description 10
- 230000000007 visual effect Effects 0.000 description 7
- 238000010586 diagram Methods 0.000 description 5
- 238000013459 approach Methods 0.000 description 4
- 238000012937 correction Methods 0.000 description 4
- 230000004927 fusion Effects 0.000 description 4
- 230000006978 adaptation Effects 0.000 description 3
- 238000006243 chemical reaction Methods 0.000 description 3
- 238000004891 communication Methods 0.000 description 3
- 230000006870 function Effects 0.000 description 3
- 238000013139 quantization Methods 0.000 description 3
- 230000008901 benefit Effects 0.000 description 2
- 239000003086 colorant Substances 0.000 description 2
- 238000007500 overflow downdraw method Methods 0.000 description 2
- 230000008447 perception Effects 0.000 description 2
- 229920001690 polydopamine Polymers 0.000 description 2
- 230000006399 behavior Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 238000007499 fusion processing Methods 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000003278 mimic effect Effects 0.000 description 1
- 238000002156 mixing Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 238000012552 review Methods 0.000 description 1
- 229920006395 saturated elastomer Polymers 0.000 description 1
- 230000035807 sensation Effects 0.000 description 1
- 230000011664 signaling Effects 0.000 description 1
- 238000001228 spectrum Methods 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
Classifications
-
- G06T5/94—
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/40—Image enhancement or restoration by the use of histogram techniques
-
- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09G—ARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION
- G09G5/00—Control arrangements or circuits for visual indicators common to cathode-ray tube indicators and other visual indicators
- G09G5/02—Control arrangements or circuits for visual indicators common to cathode-ray tube indicators and other visual indicators characterised by the way in which colour is displayed
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR 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; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20004—Adaptive image processing
- G06T2207/20012—Locally adaptive
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR 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
Definitions
- the invention relates to the tone reproduction of high dynamic range (HDR) content on low dynamic range (LDR) displays, which is also known as the tone mapping problem.
- at least one embodiment includes a method that (1) automatically generates displayable LDR images from HDR data that match the human perception of the HDR scene and (2) offers user-friendly controls for manual adjustments.
- the tone mapping problem relates to tone reproduction of high dynamic range
- HDR high dynamic range
- LDR low dynamic range
- High dynamic range has received much attention in recent years as an alternative format for digital imaging.
- the traditional Low Dynamic Range (LDR) image format was designed for displays compliant with ITU-R Recommendation BT 709 (a.k.a. Rec. 709), where only two orders of magnitude of dynamic range can be achieved.
- Real world scenes however, have a much higher dynamic range, around ten orders of magnitude in daytime, and the human visual system (HVS) is capable of perceiving 5 orders of magnitude at the same time.
- HDR displays are not mainstream devices yet; a few HDR display devices are already available as prototypes and top-of-the-line HDTVs, but the number of such displays is still very small compared to the widely used LDR displays.
- a tone mapping method is employed to map the HDR image, which is usually available as radiance, to 8bit RGB index numbers.
- the tone mapping process is not obvious because it has to simulate the process that happens in the HVS so that the tone mapped LDR image can deceive the HVS into believing it is close enough to the original HDR image. This requires the tone mapping algorithm to be able to maintain both the local contrast and the perceptual brightness.
- tone mapping for HDR image has been studied in recent years in computer graphics as well as in image/video processing communities. Roughly speaking, tone mapping methods can be classified into two primary categories: global tone mapping and local tone mapping.
- Global tone mapping uses a global curve to map radiance to image intensity.
- Tone mapping is not only studied by image processing researchers, but also by painters as well as film photographers. They face the same problem of using a limited dynamic range media (i.e. canvas for painters and print paper for photographers) to represent the high dynamic range scenes.
- a limited dynamic range media i.e. canvas for painters and print paper for photographers.
- the Zone System assigns numbers from 0 through 10 to different perceptual brightness, with 0 representing black, 5 middle gray, and 10 pure white. These values are known as zones.
- a photographer first identifies the key elements in the scene and places these elements on the desired zones. [0010] This process relies on the perception of the scene rather than the measurement of the radiance.
- a light meter is used to measure the radiance for each key element in the scene.
- an exposure value is chosen such that the most important element is mapped to the desired zone.
- other (also important) elements may be mapped to the "wrong" zone, becoming either too dark or too bright.
- this problem is fixed by applying a "dodge and burn" operation, which is a printing technique where some light is withheld from a portion of the print during development (dodge), or more light is added to that region (burn). Therefore, a key element that is mapped to a lower zone than the desired one will be exposed in the light longer than the rest part of the picture. Similarly, the key element that is mapped to a higher zone than the desired one will be exposed less. This local processing will guarantee that the key elements of the picture are mapped to the desired zone in the final output. In other words, the perceptual brightness of these key elements remains consistent with how they look like in real life.
- a method of tone mapping high dynamic range images for display on low dynamic range displays wherein a high dynamic range image is first accessed.
- the high dynamic range image is segmented then into different regions such that each region is represented by a matrix, where each element of the matrix is a weight or probability of a pixel.
- An exposure of each region is determined or calculated and the exposure values are applied to the regions responsive to the weight or probability.
- the different regions are then fused together to obtain a final tone mapped image.
- the method can further comprise the step of identifying or establishing different perceptual brightness levels for the high dynamic range images or for the final tone mapped image.
- the method can comprise any of the steps of determining regions responsive to luminance data; establishing anchor values, wherein each anchor value establishes one of the regions; and tone mapping is performed based on individual color channels. Tone mapping can be performed based on a luminance channel and then applied to color channels by post-processing and tone mapping can performed based on individual color channels.
- the method can comprise any of the steps of determining regions responsive to luminance data; establishing anchor values, wherein each anchor value establishes one of the regions; and tone mapping is performed based on individual color channels. Tone mapping can be performed based on a luminance channel and then applied to color channels by post-processing and tone mapping can performed based on individual color channels.
- Figure 1 is diagram of a known zone system scale
- Figure 2 is flow diagram of a zone based tone mapping method according to the invention.
- Figure 3 is a flow diagram of an application of the method of Figure 2 for color
- Figure 4 is a flow diagram of another application of the method of Figure 2 for color HDR images
- Figure 5 is a flow diagram showing tone correction of LDR images using themethod of Figure 2;
- Figure 6 shows a pair of sample images wherein one has been enhanced according to the methods of the invention. Detailed Description of the Embodiments
- the input and output of the tone mapping problem can be first define the input and output of the tone mapping problem.
- the input is the radiance of the scene in a known color space with known primary colors.
- the radiance data can be absolute radiance or linearly scaled radiance, which is the case when the HDR data is not calibrated.
- the output is the tone-mapped image.
- the luminance image can be computed from the HDR data. If the HDR data is in
- the Y component can be used as luminance image. If the HDR data uses the same primary colors as Rec. 709, the conversion from RGB color space may be done as follows:
- RGB or other color spaces
- luminance image can be used depending on the format of the input picture.
- A is the anchor point and S(x) can be defined as:
- p typically takes values in the range [2.2,2.4] and represents the gamma of the output device (where the tone mapped image will be shown).
- the resulting image I can be quantized and displayed on a conventional LDR display.
- S(x) e.g. an S-shaped curve can be used instead of the power function.
- any global mapping curve can be used for S.
- Zone System is then applied to digital tone mapping. As illustrated in Figure
- the input high dynamic range (HDR) image is first divided into different regions at step 10. It can be a hard segmentation or a fuzzy one. In either case, each region can be represented by a matrix, where each element of the matrix is the probability (weight) of a pixel. If a hard segmentation is used, image pixels belong to a single region and therefore the probability is either 0 or 1. If a fuzzy segmentation is used, each pixel can spread over several (even all) regions, and therefore the probability can take any value between 0 and 1.
- step 12 the algorithm decides to which zone each region will be mapped. This essentially estimates the exposure for each region. The mapping between region and zone can also be done with user interaction by providing an appropriate user interface. [0027] Next, at step 14, each region is exposed with its own exposure parameters.
- a fusion or blending process is employed to generate the final tone mapped image by fusing the different regions together (each exposed with its own exposure value) using the weights obtained in step 10.
- the user can check the look of the tone mapped image and make changes to the exposure value of one or more regions and then repeat steps 14-
- the process can be carried out for one key frame in a scene and then applied with the same parameters to all frames in the scene.
- segmentation is to divide the image into regions such that each region contains objects that should be mapped to the same zone. In other words, each region should need a single exposure.
- the segmentation can be done in a number of ways using various image processing techniques. Here a simple yet efficient approach will be described. First, the luminance image is computed from the HDR radiance data. The segmentation is carried out on the luminance image only. The average, maximum and minimum luminance of the image is then computed as follows:
- ATM min. (L) where Rmin and Rmax are two predefined percentages, maxR(X) is the smallest value in X larger or equal than R percent of the values in X, and minR(X) is the largest value in X smaller or equal than R percent of the values in X.
- pixels should have the same exposure.
- the anchor points are chosen as:
- E in the above equation is a constant and can take the value of, for example, 8.
- the number of regions N in the above equation can be computed as below, which is able to cover all the luminance range.
- the weight of each pixel is computed for each region.
- the closest the value of a pixel in the single exposure image is to 0.5, the larger the weight of that pixel for that region (defined by the corresponding anchor point A 1 ).
- the weight of pixel at location v' > 7 ) f or region n (defined by anchor point " ) can be computed as below:
- C is a normalization factor and it is defined as:
- the above computed weights take values in the range [0,1] and hence define a fuzzy segmentation of the luminance image into N regions. This means each region might contain all the pixels in the image, although only a portion of them might have large weights.
- the weights are binarized (i.e. make them either 0 or
- each region is mapped to a zone.
- an anchor point is defined for each region so that after single exposure each region can be properly exposed.
- the corresponding LDR images may be generated from the HDR data using the exposure estimated above:
- a more sophisticated fusion process combines these LDR images.
- Another image fusion method follows a multi-resolution approach using pyramids. It has higher complexity but it is much more robust to the weights (i.e. the segmentation of the image into regions) resulting in nearly seamless transition between regions.
- Figure 3 shows how the proposed zone-based tone mapping approach 300 can be used to tone map color HDR images.
- the luminance image is computed using the equation provided above.
- luminance image is processed according to the described method framework.
- the color processing step applies the tone mapping of the luminance image to each color component.
- the color processing step scales each pixel of each color component by the same amount wherein the corresponding pixel of the luminance image has been scaled, and then performs gamma correction and quantization. This process is summarized by the following equations:
- Tone correction of color LDR images may be accomplished using the zone based tone mapping methods described above. These methods may be applied to automatically or manually correct LDR images. As illustrated in process flow 500 of Figure 5, an additional step compared to the processing of HDR images is the conversion from LDR to HDR, which can be done using inverse quantization and inverse gamma transform:
- tone mapping may be performed on each color component independently (e.g. a red color mapping flow 401, green color mapping flow 402, and blue color mapping flow 403 , instead of using the luminance image as best shown in Figure 4.
- tone mapping may be performed on a color component, instead of using the luminance image.
- a single component e.g., one of the color components or luminance image
- color components may be used in other steps. For instance, luminance for steps 10-12, and color components for steps 14-16.
- these implementations and features may be used in the context of coding video and/or coding other types of data. Additionally, these implementations and features may be used in the context of, or adapted for use in the context of, the H.264/MPEG-4 AVC (AVC) Standard, the AVC standard with the MVC extension, the AVC standard with the SVC extension, a 3DV standard, and/or with another standard (existing or future), or in a context that does not involve a standard.
- AVC H.264/MPEG-4 AVC
- implementations may signal information using a variety of techniques including, but not limited to, SEI messages, slice headers, other high level syntax, non-high-level syntax, out-of-band information, datastream data, and implicit signaling.
- An apparatus may be implemented in, for example, appropriate hardware, software, and firmware.
- the methods may be implemented in, for example, an apparatus such as, for example, a processor, which refers to processing devices in general, including, for example, a computer, a microprocessor, an integrated circuit, or a programmable logic device.
- processors also include communication devices, such as, for example, computers, cell phones, portable/personal digital assistants ("PDAs"), and other devices that facilitate communication of information between end-users.
- PDAs portable/personal digital assistants
- Implementations of the various processes and features described herein may be embodied in a variety of different equipment or applications, particularly, for example, equipment or applications associated with data encoding and decoding.
- equipment include an encoder, a decoder, a post-processor processing output from a decoder, a pre-processor providing input to an encoder, a video coder, a video decoder, a video codec, a web server, a set-top box, a laptop, a personal computer, a cell phone, a PDA, and other communication devices.
- the equipment may be mobile and even installed in a mobile vehicle.
- the methods may be implemented by instructions being performed by a processor, and such instructions (and/or data values produced by an implementation) may be stored on a processor-readable medium such as, for example, an integrated circuit, a software carrier or other storage device such as, for example, a hard disk, a compact diskette, a random access memory ("RAM"), or a read-only memory (“ROM").
- the instructions may form an application program tangibly embodied on a processor-readable medium. Instructions may be, for example, in hardware, firmware, software, or a combination. Instructions may be found in, for example, an operating system, a separate application, or a combination of the two.
- a processor may be characterized, therefore, as, for example, both a device configured to carry out a process and a device that includes a processor-readable medium (such as a storage device) having instructions for carrying out a process. Further, a processor-readable medium may store, in addition to or in lieu of instructions, data values produced by an implementation.
- implementations may produce a variety of signals formatted to carry information that may be, for example, stored or transmitted.
- the information may include, for example, instructions for performing a method, or data produced by one of the described implementations.
- a signal may be formatted to carry as data the rules for writing or reading the syntax of a described embodiment, or to carry as data the actual syntax-values written by a described embodiment.
- Such a signal may be formatted, for example, as an electromagnetic wave (for example, using a radio frequency portion of spectrum) or as a baseband signal.
- the formatting may include, for example, encoding a data stream and modulating a carrier with the encoded data stream.
- the information that the signal carries may be, for example, analog or digital information.
- the signal may be transmitted over a variety of different wired or wireless links, as is known.
- the signal may be stored on a processor-readable medium.
Abstract
Description
Claims
Priority Applications (5)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
KR1020117031365A KR101739432B1 (en) | 2009-06-29 | 2010-06-29 | Zone-based tone mapping |
EP10736865A EP2449526A1 (en) | 2009-06-29 | 2010-06-29 | Zone-based tone mapping |
US13/381,224 US9087382B2 (en) | 2009-06-29 | 2010-06-29 | Zone-based tone mapping |
JP2012517502A JP5611337B2 (en) | 2009-06-29 | 2010-06-29 | Zone-based tone mapping |
CN201080029221.1A CN102473295B (en) | 2009-06-29 | 2010-06-29 | Based on the tone mapping in district |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US26976009P | 2009-06-29 | 2009-06-29 | |
US61/269,760 | 2009-06-29 |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2011002505A1 true WO2011002505A1 (en) | 2011-01-06 |
Family
ID=42542728
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/US2010/001863 WO2011002505A1 (en) | 2009-06-29 | 2010-06-29 | Zone-based tone mapping |
Country Status (6)
Country | Link |
---|---|
US (1) | US9087382B2 (en) |
EP (1) | EP2449526A1 (en) |
JP (1) | JP5611337B2 (en) |
KR (1) | KR101739432B1 (en) |
CN (1) | CN102473295B (en) |
WO (1) | WO2011002505A1 (en) |
Cited By (13)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102497490A (en) * | 2011-12-16 | 2012-06-13 | 上海富瀚微电子有限公司 | System and method for realizing image high dynamic range compression |
CN103891294A (en) * | 2011-04-28 | 2014-06-25 | 皇家飞利浦有限公司 | Apparatuses and methods for hdr image encoding and decodng |
WO2014118033A1 (en) * | 2013-01-29 | 2014-08-07 | Thomson Licensing | Method and device for modifying the dynamic range of an image sequence |
WO2013144809A3 (en) * | 2012-03-26 | 2015-02-19 | Koninklijke Philips N.V. | Brightness region-based apparatuses and methods for hdr image encoding and decoding |
US9009119B2 (en) | 2011-11-11 | 2015-04-14 | International Business Machines Corporation | Compressing a multivariate dataset |
WO2015128295A1 (en) * | 2014-02-26 | 2015-09-03 | Thomson Licensing | Method and apparatus for encoding and decoding hdr images |
EP2927865A1 (en) * | 2014-04-01 | 2015-10-07 | Thomson Licensing | Method and apparatus for encoding and decoding HDR images |
US9501816B2 (en) | 2012-05-10 | 2016-11-22 | National Ict Australia Limited | Reducing the dynamic range of image data |
EP3113492A1 (en) | 2015-06-30 | 2017-01-04 | Thomson Licensing | Method and apparatus for determining prediction of current block of enhancement layer |
EP3301925A1 (en) | 2016-09-30 | 2018-04-04 | Thomson Licensing | Method for local inter-layer prediction intra based |
WO2019045727A1 (en) * | 2017-08-31 | 2019-03-07 | Sony Mobile Communications Inc. | Methods, devices, and computer program products for checking environment acceptability for 3d scanning |
CN110400269A (en) * | 2019-07-04 | 2019-11-01 | 汕头大学 | A kind of quick HDR image tone mapping method |
CN112468737A (en) * | 2020-11-25 | 2021-03-09 | 上海摩象网络科技有限公司 | Method and device for processing exposure weight matrix of automatic exposure area |
Families Citing this family (54)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102763134B (en) * | 2010-02-19 | 2015-11-25 | 汤姆森特许公司 | For the parameter interpolate of high dynamic range video tone mapping |
US8786625B2 (en) * | 2010-09-30 | 2014-07-22 | Apple Inc. | System and method for processing image data using an image signal processor having back-end processing logic |
US8675957B2 (en) * | 2010-11-18 | 2014-03-18 | Ebay, Inc. | Image quality assessment to merchandise an item |
US20120293533A1 (en) * | 2011-05-19 | 2012-11-22 | Foveon Inc. | Methods for creating gamma correction and tone mapping effects in a digital image |
JP5713885B2 (en) * | 2011-12-26 | 2015-05-07 | キヤノン株式会社 | Image processing apparatus, image processing method, program, and storage medium |
US8817120B2 (en) | 2012-05-31 | 2014-08-26 | Apple Inc. | Systems and methods for collecting fixed pattern noise statistics of image data |
US9077943B2 (en) | 2012-05-31 | 2015-07-07 | Apple Inc. | Local image statistics collection |
US11089247B2 (en) | 2012-05-31 | 2021-08-10 | Apple Inc. | Systems and method for reducing fixed pattern noise in image data |
US8917336B2 (en) | 2012-05-31 | 2014-12-23 | Apple Inc. | Image signal processing involving geometric distortion correction |
US8872946B2 (en) | 2012-05-31 | 2014-10-28 | Apple Inc. | Systems and methods for raw image processing |
US9332239B2 (en) | 2012-05-31 | 2016-05-03 | Apple Inc. | Systems and methods for RGB image processing |
US9142012B2 (en) | 2012-05-31 | 2015-09-22 | Apple Inc. | Systems and methods for chroma noise reduction |
US9743057B2 (en) | 2012-05-31 | 2017-08-22 | Apple Inc. | Systems and methods for lens shading correction |
US8953882B2 (en) | 2012-05-31 | 2015-02-10 | Apple Inc. | Systems and methods for determining noise statistics of image data |
US9025867B2 (en) | 2012-05-31 | 2015-05-05 | Apple Inc. | Systems and methods for YCC image processing |
US9105078B2 (en) | 2012-05-31 | 2015-08-11 | Apple Inc. | Systems and methods for local tone mapping |
US9014504B2 (en) | 2012-05-31 | 2015-04-21 | Apple Inc. | Systems and methods for highlight recovery in an image signal processor |
US9031319B2 (en) | 2012-05-31 | 2015-05-12 | Apple Inc. | Systems and methods for luma sharpening |
CN103024300B (en) * | 2012-12-25 | 2015-11-25 | 华为技术有限公司 | A kind of method for high dynamic range image display and device |
WO2014118032A1 (en) * | 2013-01-29 | 2014-08-07 | Thomson Licensing | Method and device for modifying the dynamic range of an image |
WO2014128586A1 (en) * | 2013-02-21 | 2014-08-28 | Koninklijke Philips N.V. | Improved hdr image encoding and decoding methods and devices |
CN103281537B (en) * | 2013-05-23 | 2016-06-08 | 华为技术有限公司 | A kind of dynamic range of images compression method and device |
US8958658B1 (en) | 2013-09-10 | 2015-02-17 | Apple Inc. | Image tone adjustment using local tone curve computation |
EP2894857A1 (en) * | 2014-01-10 | 2015-07-15 | Thomson Licensing | Method and apparatus for encoding image data and method and apparatus for decoding image data |
US9420145B2 (en) * | 2014-01-13 | 2016-08-16 | Marvell World Trade Ltd. | System and method for tone mapping of images |
US9344638B2 (en) * | 2014-05-30 | 2016-05-17 | Apple Inc. | Constant bracket high dynamic range (cHDR) operations |
US9460499B2 (en) * | 2014-05-30 | 2016-10-04 | Shenzhen Mindray Bio-Medical Electronics Co., Ltd. | Systems and methods for selective enhancement of a region of interest in an image |
US9380218B2 (en) | 2014-05-30 | 2016-06-28 | Apple Inc. | Highlight exposure metric and its applications |
US9773473B2 (en) * | 2014-06-03 | 2017-09-26 | Nvidia Corporation | Physiologically based adaptive image generation |
GB201410635D0 (en) * | 2014-06-13 | 2014-07-30 | Univ Bangor | Improvements in and relating to the display of images |
CN107533832B (en) * | 2015-05-12 | 2020-11-27 | 索尼公司 | Image processing apparatus, image processing method, and program |
WO2016192937A1 (en) * | 2015-05-29 | 2016-12-08 | Thomson Licensing | Methods, apparatus, and systems for hdr tone mapping operator |
US10885614B2 (en) | 2015-08-19 | 2021-01-05 | Samsung Electronics Co., Ltd. | Electronic device performing image conversion, and method thereof |
US9621767B1 (en) | 2015-11-24 | 2017-04-11 | Intel Corporation | Spatially adaptive tone mapping for display of high dynamic range (HDR) images |
CN105744157A (en) * | 2016-02-02 | 2016-07-06 | 西安电子科技大学 | Image pixel sampling value conversion method and device as well as sampling value processing method and device |
WO2017153376A1 (en) * | 2016-03-07 | 2017-09-14 | Koninklijke Philips N.V. | Encoding and decoding hdr videos |
CN107292829B (en) * | 2016-03-31 | 2020-12-15 | 阿里巴巴集团控股有限公司 | Image processing method and device |
US20170289571A1 (en) * | 2016-04-01 | 2017-10-05 | Intel Corporation | Temporal control for spatially adaptive tone mapping of high dynamic range video |
US10129485B2 (en) | 2016-06-10 | 2018-11-13 | Microsoft Technology Licensing, Llc | Methods and systems for generating high dynamic range images |
US10074162B2 (en) | 2016-08-11 | 2018-09-11 | Intel Corporation | Brightness control for spatially adaptive tone mapping of high dynamic range (HDR) images |
JP7054851B2 (en) * | 2016-09-09 | 2022-04-15 | パナソニックIpマネジメント株式会社 | Display device and signal processing method |
JP6824817B2 (en) * | 2017-05-17 | 2021-02-03 | キヤノン株式会社 | Image processing device and image processing method |
US10504263B2 (en) | 2017-08-01 | 2019-12-10 | Samsung Electronics Co., Ltd. | Adaptive high dynamic range (HDR) tone mapping with overlay indication |
CN107886479A (en) * | 2017-10-31 | 2018-04-06 | 建荣半导体(深圳)有限公司 | A kind of image HDR conversion methods, device, picture processing chip and storage device |
EP3493150A1 (en) * | 2017-11-30 | 2019-06-05 | InterDigital VC Holdings, Inc. | Tone mapping adaptation for saturation control |
US10546554B2 (en) | 2018-03-26 | 2020-01-28 | Dell Products, Lp | System and method for adaptive tone mapping for high dynamic ratio digital images |
JP7117915B2 (en) * | 2018-06-29 | 2022-08-15 | キヤノン株式会社 | Image processing device, control method, and program |
EP3594894A1 (en) * | 2018-07-11 | 2020-01-15 | InterDigital VC Holdings, Inc. | Tone-mapping of colors of a video content |
EP3661188B1 (en) * | 2018-11-27 | 2020-10-28 | Axis AB | A method for reducing intensity variations in a video image stream depicting a scene |
EP3959646B1 (en) * | 2019-04-25 | 2023-04-19 | Dolby Laboratories Licensing Corporation | Content-aware pq range analyzer and tone mapping in live feeds |
US11473971B2 (en) | 2019-09-27 | 2022-10-18 | Apple Inc. | Ambient headroom adaptation |
CN111080565B (en) * | 2019-12-11 | 2023-07-18 | 九江学院 | Exposure fusion method, device and storage medium based on image quality change rule |
CN111784607A (en) * | 2020-06-30 | 2020-10-16 | Oppo广东移动通信有限公司 | Image tone mapping method, device, terminal equipment and storage medium |
WO2022151320A1 (en) * | 2021-01-15 | 2022-07-21 | 深圳市大疆创新科技有限公司 | Image processing method and apparatus, and computer-readable storage medium |
Citations (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20060262363A1 (en) * | 2005-05-23 | 2006-11-23 | Canon Kabushiki Kaisha | Rendering of high dynamic range images |
Family Cites Families (30)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE69214229T2 (en) | 1991-08-14 | 1997-04-30 | Agfa Gevaert Nv | Method and device for improving the contrast of images |
US5717789A (en) | 1993-09-08 | 1998-02-10 | California Institute Of Technology | Image enhancement by non-linear extrapolation in frequency space |
GB9626676D0 (en) | 1996-12-23 | 1997-02-12 | Smith & Nephew Res | Imaging method |
NZ332626A (en) | 1997-11-21 | 2000-04-28 | Matsushita Electric Ind Co Ltd | Expansion of dynamic range for video camera |
US6359617B1 (en) | 1998-09-25 | 2002-03-19 | Apple Computer, Inc. | Blending arbitrary overlaying images into panoramas |
US6775407B1 (en) | 2000-08-02 | 2004-08-10 | Eastman Kodak Company | Producing a final modified digital image using a source digital image and a difference digital image |
JP4556319B2 (en) * | 2000-10-27 | 2010-10-06 | ソニー株式会社 | Image processing apparatus and method, and recording medium |
US6879731B2 (en) | 2003-04-29 | 2005-04-12 | Microsoft Corporation | System and process for generating high dynamic range video |
US20050117799A1 (en) | 2003-12-01 | 2005-06-02 | Chiou-Shann Fuh | Method and apparatus for transforming a high dynamic range image into a low dynamic range image |
JP3956311B2 (en) * | 2004-02-19 | 2007-08-08 | オムロン株式会社 | Image data conversion device and camera device |
JP2006215756A (en) * | 2005-02-02 | 2006-08-17 | Dainippon Ink & Chem Inc | Image processing apparatus, image processing method, and program for the same |
US7623724B2 (en) * | 2005-03-16 | 2009-11-24 | Fabio Riccardi | Interface method and system for mapping image intensity |
US7492962B2 (en) | 2005-08-25 | 2009-02-17 | Delphi Technologies, Inc. | System or method for enhancing an image |
US7821570B2 (en) | 2005-11-30 | 2010-10-26 | Eastman Kodak Company | Adjusting digital image exposure and tone scale |
JP2007193585A (en) * | 2006-01-19 | 2007-08-02 | Konica Minolta Photo Imaging Inc | Image processing method, display controller, reception terminal, and image processing program |
CN101742306A (en) | 2006-01-23 | 2010-06-16 | 马普科技促进协会 | High dynamic range codecs |
US7636496B2 (en) | 2006-05-17 | 2009-12-22 | Xerox Corporation | Histogram adjustment for high dynamic range image mapping |
JP4267025B2 (en) * | 2006-11-27 | 2009-05-27 | 三菱電機株式会社 | Video display device |
CN100461218C (en) | 2007-03-29 | 2009-02-11 | 杭州电子科技大学 | Method for enhancing medical image with multi-scale self-adaptive contrast change |
JP5041876B2 (en) | 2007-05-22 | 2012-10-03 | 株式会社日立製作所 | Digital broadcast receiver |
JP5188101B2 (en) | 2007-06-01 | 2013-04-24 | 株式会社キーエンス | Magnification observation apparatus, magnified image photographing method, magnified image photographing program, and computer-readable recording medium |
CN101082992A (en) * | 2007-07-06 | 2007-12-05 | 浙江大学 | Drawing of real time high dynamic range image and display process |
JP5142614B2 (en) * | 2007-07-23 | 2013-02-13 | 富士フイルム株式会社 | Image playback device |
US8135230B2 (en) | 2007-07-30 | 2012-03-13 | Dolby Laboratories Licensing Corporation | Enhancing dynamic ranges of images |
US8233738B2 (en) | 2007-07-30 | 2012-07-31 | Dolby Laboratories Licensing Corporation | Enhancing dynamic ranges of images |
DE102007041022A1 (en) | 2007-08-29 | 2009-03-05 | Niro-Plan Ag | Apparatus and method for preparing flavored hot drinks, in particular coffee and tea |
US8411938B2 (en) | 2007-11-29 | 2013-04-02 | Sri International | Multi-scale multi-camera adaptive fusion with contrast normalization |
US7471826B1 (en) | 2008-03-31 | 2008-12-30 | International Business Machines Corporation | Character segmentation by slices |
US8346009B2 (en) | 2009-06-29 | 2013-01-01 | Thomson Licensing | Automatic exposure estimation for HDR images based on image statistics |
JP5655334B2 (en) * | 2010-03-19 | 2015-01-21 | ソニー株式会社 | Image processing apparatus and method, and program |
-
2010
- 2010-06-29 WO PCT/US2010/001863 patent/WO2011002505A1/en active Application Filing
- 2010-06-29 JP JP2012517502A patent/JP5611337B2/en active Active
- 2010-06-29 EP EP10736865A patent/EP2449526A1/en not_active Withdrawn
- 2010-06-29 US US13/381,224 patent/US9087382B2/en active Active
- 2010-06-29 KR KR1020117031365A patent/KR101739432B1/en active IP Right Grant
- 2010-06-29 CN CN201080029221.1A patent/CN102473295B/en active Active
Patent Citations (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20060262363A1 (en) * | 2005-05-23 | 2006-11-23 | Canon Kabushiki Kaisha | Rendering of high dynamic range images |
Non-Patent Citations (6)
Title |
---|
DEVLIN K ET AL: "Dynamic Range Reduction Inspired by Photoreceptor Physiology", IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, vol. 11, no. 1, 1 January 2005 (2005-01-01), IEEE SERVICE CENTER, LOS ALAMITOS, CA, US, pages 13 - 24, XP011122132, ISSN: 1077-2626, DOI: 10.1109/TVCG.2005.9 * |
KRAWCZYK G ET AL: "Computational model of lightness perception in high dynamic range imaging", PROCEEDINGS OF SPIE - HUMAN VISION AND ELECTRONIC IMAGING XI - IS AND T ELECTRONIC IMAGING, vol. 6057, 2006, SPIE US, XP002596494, DOI: 10.1117/12.639266 * |
LISCHINSKI D ET AL: "Interactive local adjustment of tonal values", ACM SIGGRAPH 2006 PAPERS, SIGGRAPH '06, 2006, ASSOCIATION FOR COMPUTING MACHINERY USA, pages 646 - 653, XP002596495, DOI: 10.1145/1179352.1141936 * |
REINHARD E ET AL: "Photographic tone reproduction for digital images", ACM TRANSACTIONS ON GRAPHICS, vol. 21, no. 3, 1 July 2002 (2002-07-01), ACM, US, pages 267 - 276, XP007904044, ISSN: 0730-0301, DOI: 10.1145/566570.566575 * |
See also references of EP2449526A1 |
YEE Y H ET AL: "Segmentation and adaptive assimilation for detail-preserving display of high-dynamic range images", VISUAL COMPUTER, vol. 19, no. 7-8, 1 December 2003 (2003-12-01), SPRINGER, BERLIN, DE, pages 457 - 466, XP008106258, ISSN: 0178-2789, [retrieved on 20030708], DOI: 10.1007/S00371-003-0211-5 * |
Cited By (23)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103891294A (en) * | 2011-04-28 | 2014-06-25 | 皇家飞利浦有限公司 | Apparatuses and methods for hdr image encoding and decodng |
CN103891294B (en) * | 2011-04-28 | 2017-09-01 | 皇家飞利浦有限公司 | The apparatus and method coded and decoded for HDR image |
US9009119B2 (en) | 2011-11-11 | 2015-04-14 | International Business Machines Corporation | Compressing a multivariate dataset |
CN102497490B (en) * | 2011-12-16 | 2014-08-13 | 上海富瀚微电子有限公司 | System and method for realizing image high dynamic range compression |
CN102497490A (en) * | 2011-12-16 | 2012-06-13 | 上海富瀚微电子有限公司 | System and method for realizing image high dynamic range compression |
CN104541301A (en) * | 2012-03-26 | 2015-04-22 | 皇家飞利浦有限公司 | Brightness region-based apparatuses and methods for hdr image encoding and decoding |
US10057600B2 (en) | 2012-03-26 | 2018-08-21 | Koninklijke Philips N.V. | Brightness region-based apparatuses and methods for HDR image encoding and decoding |
WO2013144809A3 (en) * | 2012-03-26 | 2015-02-19 | Koninklijke Philips N.V. | Brightness region-based apparatuses and methods for hdr image encoding and decoding |
US9501816B2 (en) | 2012-05-10 | 2016-11-22 | National Ict Australia Limited | Reducing the dynamic range of image data |
WO2014118033A1 (en) * | 2013-01-29 | 2014-08-07 | Thomson Licensing | Method and device for modifying the dynamic range of an image sequence |
WO2015128295A1 (en) * | 2014-02-26 | 2015-09-03 | Thomson Licensing | Method and apparatus for encoding and decoding hdr images |
US11727548B2 (en) | 2014-02-26 | 2023-08-15 | Interdigital Vc Holdings, Inc. | Method and apparatus for encoding and decoding HDR images |
US10650501B2 (en) | 2014-02-26 | 2020-05-12 | Interdigital Vc Holdings, Inc. | Method and apparatus for encoding and decoding HDR images |
EP2927865A1 (en) * | 2014-04-01 | 2015-10-07 | Thomson Licensing | Method and apparatus for encoding and decoding HDR images |
EP3113492A1 (en) | 2015-06-30 | 2017-01-04 | Thomson Licensing | Method and apparatus for determining prediction of current block of enhancement layer |
WO2018060051A1 (en) | 2016-09-30 | 2018-04-05 | Thomson Licensing | Method for local inter-layer prediction intra based |
EP3301925A1 (en) | 2016-09-30 | 2018-04-04 | Thomson Licensing | Method for local inter-layer prediction intra based |
WO2019045727A1 (en) * | 2017-08-31 | 2019-03-07 | Sony Mobile Communications Inc. | Methods, devices, and computer program products for checking environment acceptability for 3d scanning |
US11158036B2 (en) | 2017-08-31 | 2021-10-26 | Sony Group Corporation | Methods, devices, and computer program products for checking environment acceptability for 3D scanning |
CN110400269A (en) * | 2019-07-04 | 2019-11-01 | 汕头大学 | A kind of quick HDR image tone mapping method |
CN110400269B (en) * | 2019-07-04 | 2021-08-06 | 汕头大学 | Rapid HDR image tone mapping method |
CN112468737A (en) * | 2020-11-25 | 2021-03-09 | 上海摩象网络科技有限公司 | Method and device for processing exposure weight matrix of automatic exposure area |
CN112468737B (en) * | 2020-11-25 | 2022-04-29 | 上海摩象网络科技有限公司 | Method and device for processing exposure weight matrix of automatic exposure area |
Also Published As
Publication number | Publication date |
---|---|
US9087382B2 (en) | 2015-07-21 |
KR20120107429A (en) | 2012-10-02 |
CN102473295B (en) | 2016-05-04 |
KR101739432B1 (en) | 2017-05-24 |
JP2012532335A (en) | 2012-12-13 |
CN102473295A (en) | 2012-05-23 |
EP2449526A1 (en) | 2012-05-09 |
US20120113130A1 (en) | 2012-05-10 |
JP5611337B2 (en) | 2014-10-22 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US9087382B2 (en) | Zone-based tone mapping | |
US8346009B2 (en) | Automatic exposure estimation for HDR images based on image statistics | |
US10419762B2 (en) | Content-adaptive perceptual quantizer for high dynamic range images | |
EP3220350B1 (en) | Methods, apparatus, and systems for extended high dynamic range hdr to hdr tone mapping | |
EP3566203B1 (en) | Perceptually preserving scene-referred contrasts and chromaticities | |
Myszkowski et al. | High dynamic range video | |
US20120082397A1 (en) | Contrast enhancement | |
CN107771392B (en) | Real-time content adaptive perceptual quantizer for high dynamic range images | |
CN107888943B (en) | Image processing | |
JP2015122110A (en) | High dynamic range image generation and rendering | |
EP3323104B1 (en) | A method and device for tone-mapping a picture by using a parametric tone-adjustment function | |
WO2018231968A1 (en) | Efficient end-to-end single layer inverse display management coding | |
US20230370646A1 (en) | Adaptive local reshaping for sdr-to-hdr up-conversion | |
CN107087163A (en) | A kind of coding method of lifting HDR Subjective video qualities | |
CN111724316B (en) | Method and apparatus for processing high dynamic range image | |
Koz et al. | Methods for improving the tone mapping for backward compatible high dynamic range image and video coding | |
CN111105376A (en) | Single-exposure high-dynamic-range image generation method based on double-branch neural network | |
CN110770787B (en) | Efficient end-to-end single-layer reverse display management coding | |
Chen et al. | Tone reproduction: A perspective from luminance-driven perceptual grouping | |
Vo et al. | HDR10+ adaptive ambient compensation using creative intent metadata | |
Narwaria et al. | High dynamic range visual quality of experience measurement: Challenges and perspectives | |
CN113411553A (en) | Image processing method, image processing device, electronic equipment and storage medium | |
Lee et al. | Piecewise tone reproduction for high dynamic range imaging | |
Abebe | High Dynamic Range Imaging | |
Cyriac et al. | Automatic, viewing-condition dependent contrast grading based on perceptual models |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
WWE | Wipo information: entry into national phase |
Ref document number: 201080029221.1 Country of ref document: CN |
|
121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 10736865 Country of ref document: EP Kind code of ref document: A1 |
|
WWE | Wipo information: entry into national phase |
Ref document number: 2010736865 Country of ref document: EP |
|
WWE | Wipo information: entry into national phase |
Ref document number: 2012517502 Country of ref document: JP |
|
ENP | Entry into the national phase |
Ref document number: 20117031365 Country of ref document: KR Kind code of ref document: A |
|
WWE | Wipo information: entry into national phase |
Ref document number: 13381224 Country of ref document: US |
|
NENP | Non-entry into the national phase |
Ref country code: DE |