This application claims the benefit, under 35 U.S.C. § 365 of International Application PCT/US2019/030103, filed May 1, 2019 which was published in accordance with PCT Article 21(2) on Jan. 16, 2019, in English, and which claims the benefit of European Patent Application No. 18305931.0, filed Jul. 11, 2018
The invention relates to mapping of tones or colors of images. Tone-mapping is understood as a generic term including a tone-mapping that compresses a color range and a tone-mapping that expands a color range (generally named “inverse tone-mapping”).
The document EP3249606 discloses, for the processing of an image, the selection of an inverse Tone Mapping (iTM) algorithm among a reference collection of reference iTM algorithms and the application of the selected ITM algorithm to colors of this image, notably to convert this image into a HDR format. According to this method, a collection of reference iTM algorithms is built. Any reference iTM algorithm of this collection is an iTM algorithm which is optimized to color content of associated reference images. According to this method, a visual feature is associated with each reference iTM algorithm, based on the color content of the reference image(s) associated with this reference iTM algorithm. According to this method as illustrated on
When applying such an image processing method to images of a video content, the video content should be cut into shots such that, within each shot, the color content is homogenous enough to apply the same selected iTM algorithm to each image of the shot.
In order to prevent too frequent changes of iTM algorithm inside a video shot that would cause temporal instabilities and visual discomfort during visualization, it is proposed to add, after the selection of a reference iTM for an image of the shot, a step of validation of this selection for the next images of this shot.
Preferably, it is also proposed to apply progressively any change of iTM algorithm as soon as it is validated.
Note that the document U.S. Pat. No. 9,406,112 discloses changing a Tone Mapping (TM) function only when the difference between a previous and a new TM function is large enough. WO2016192937 considers the full history of previous TM curves applied to previous frames to parametrize a new TM curve to apply to a current frame. In US20170070719, a tone mapping system may use an average of previous tone curve parameter values.
More precisely, a first aspect of the disclosure is directed to a method for tone or color mapping images of a video content according to a tone mapping function, comprising iterating on a plurality of successive images of the video content and for at least one image of the plurality of successive images: selecting in a reference collection of tone-mapping functions a reference tone-mapping function according to a visual feature determined from said at least one image; when the selected reference tone mapping function is different from a previously selected tone mapping function for the previous image in the plurality of successive images, determining a reference tone mapping function according to a validation step; and applying the determined reference tone-mapping function to said at least one image resulting into a corresponding tone-mapped image, wherein the reference collection comprises reference tone-mapping functions associated with reference visual features.
In variants of the first aspect, the validation step uses a plurality of successive images and either selects the reference tone mapping function determined for the successive images that is the most frequent, or selects a reference tone mapping function according to a number of consecutive selections of a same reference tone mapping function or selects the reference tone mapping function with increasing occurrence compared to the other reference tone mapping functions.
In a further variant of first aspect, selecting a reference tone-mapping function is done according to a selection criterion based on a minimum distance between the visual feature of the image and the reference visual feature associated with this selected reference tone-mapping function. In a further variant of first aspect, the transition between a first reference tone mapping function and a second reference tone mapping function is done progressively over a plurality of images by varying the weights between both functions, the weight of the first function decreasing during the transition and the weight of the second function increasing during the transition. In a further variant of first aspect, for the first image of the video, the selected reference tone mapping function does not require any validation step and is applied to the first image of the video.
A second aspect of the disclosure is directed to a device for tone or color mapping images of a video content according to a tone mapping function, comprising at least one processor configured for implementing the above method. Preferably, this device is chosen in the group composed of a mobile device, a communication device, a game device, a tablet, a laptop, a camera, a chip, a server, a TV set and a Set-Top Box.
A third aspect of the disclosure is directed to a computable readable storage medium comprising stored instructions that when executed by a processor performs the above method.
The invention will be more clearly understood on reading the description which follows, given by way of non-limiting example and with reference to the appended figures in which:
The functions of the various elements shown in the figures may be provided through the use of dedicated hardware as well as hardware capable of executing software in association with appropriate software. Explicit use of the term “processor” should not be construed to refer exclusively to hardware capable of executing software, and may implicitly include, without limitation, digital signal processor (“DSP”) hardware, read-only memory (“ROM”) for storing software, random access memory (“RAM”), and non-volatile storage.
Any switches shown in the figures are conceptual only. Their function may be carried out through the operation of program logic, through dedicated logic, through the interaction of program control and dedicated logic, or even manually, the particular technique being selectable by the implementer as more specifically understood from the context.
It is to be understood that the image processing method may be implemented in various forms of hardware, software, firmware, special purpose processors, or combinations thereof. This method may be notably implemented as a combination of hardware and software. Moreover, the software may be implemented as an application program tangibly embodied on a program storage unit. The application program may be uploaded to, and executed by, a computing machine comprising any suitable architecture. Preferably, the machine is implemented on an apparatus having hardware such as one or more central processing units (“CPU”), a random access memory (“RAM”), and input/output (“I/O”) interfaces. The apparatus may also include an operating system and microinstruction code. The various processes and functions described herein may be either part of the microinstruction code or part of the application program, or any combination thereof, which may be executed by a CPU. In addition, various other peripheral units may be connected to the apparatus such as an actual or virtual keyboard, a display device and an additional data storage unit.
As a whole, this apparatus may notably be a mobile device (such as a smartphone), a communication device, a game device, a tablet (or tablet computer), a laptop, a TV set, a Set-Top-Box, a camera, an encoding chip or a server (e.g. a broadcast server, a video-on-demand server or a web server).
A main embodiment of the image processing method will now be described, using an apparatus as described above having at least one processor and at least one memory configured in a manner known per se to implement this method.
The memory stores a reference collection of reference tone-mapping algorithms and associated visual features. Tone-mapping is a generic term including tone-mapping that compresses a color range and tone-mapping that expands a color range (generally named “inverse tone-mapping”). This reference collection is for instance built as disclosed in EP3249606 as follows:
Building such a collection of reference tone-mapping functions and associated reference visual features can be performed “off-line”—in the same platform or in another platform—during a preliminary training phase comprising:
The image processing method will now be described in reference to
The memory receives, preferably in a buffer, images of the video content to be tone-mapped.
For a first image of the content, in the reference collection of reference tone-mapping functions, a reference tone-mapping function is selected according to a selection criterion based on a minimum distance between the reference visual feature associated with this selected reference tone-mapping function and the visual feature of this first image. For instance, a distance is computed between each reference visual feature of the collection and the visual feature of the first image. When the visual feature is a histogram of values of luminance as described above, the shortest computed distance indicates that the distribution of luminance values within the first image is close to a reference distribution of luminance values of the collection, and the reference tone-mapping function associated with this close reference distribution of luminance values is selected. Then, the selected reference tone-mapping function is applied to the first image resulting into a corresponding tone-mapped first image.
The application of the selected reference tone-mapping function is reiterated from image to image of the content, i.e. from a previous image to a following image, as far as the reference tone-mapping function selected for a following image is the same as the reference tone-mapping function selected for the previous image.
As soon as reference tone-mapping function TMfN selected for a following image IMN is different from a reference tone-mapping function TMfP selected for a previous image IMP (this situation is represented on
Then a validation step is launched as follows for the i+1 images IMN, IMN+1, . . . , IMk, . . . , IMN+i of the content. The number i+1 of images used for the validation of a change or non-change of tone-mapping function is superior to 2. For instance, for a frame rate of 25 images/second, i+1=5.
This validation step aims at making a decision to change the tone-mapping function or not to change the tone-mapping function and, in case a change is decided, to validate a “right” new reference tone-mapping function to be applied to images of the sequence, with, optionally, a transition step in between (see below).
Prior to the validation step itself, based on the same selection criterion as above, a reference tone-mapping function TMfN+1, . . . , TMfk, . . . , TMfN+i is selected in the collection of reference tone-mapping functions for each of the i last images IMN+1, . . . , IMk, . . . , IMN+i of the current validation sequence.
Once all reference tone-mapping functions TMfN, TMfN+1, TMfN+2, TMfN+3, TMfN+4, TMfN+5, . . . , TMfk−1, TMfk, TMfk+1, . . . , TMfN+i are selected for all images of the current validation sequence, the validation step is performed according to a validation criterion, preferably based on a distribution of these selected tone-mapping functions.
Assuming for instance i=9 and k=N+7, then the ten reference tone-mapping functions are listed as follows: TMfN, TMfN+1, TMfN+2, TMfN+3, TMfN+4, TMfN+5, TMfk−1, TMfk, TMfk+1, TMfN+i.
Let assume for instance that, in this list, there are only two different reference tone-mapping functions: P1 and P2, and that the distribution is as follows: TMfN=P2, TMfN+1=P1, TMfN+2=P1, TMfN+3=P2, TMfN+4=P2, TMfN+5=P2, TMfk−1=P1, TMfk=P2, TMfk+1=P2, TMfN+i=P2.
In this situation (distribution=P2P1P1P2P2P2P1P2P2P2), the two different reference tone-mapping functions P1 and P2 are distributed over two bins, a first bin for P1 with a value of 3, and a second bin for P2 with a value of 7.
The validation criterion is for instance defined such the reference tone-mapping function having the most populated bin in the distribution is validated, here P2 corresponding notably with TMfk.
As a first variant, the validation criterion is based on a minimum of consecutive selection of a same reference tone-mapping function within the different images of the validation sequence. For instance, within the same validation sequence of 10 images (i=9) as above, this minimum could be fixed to a value of 4, leading to a validation of the same reference tone-mapping function TMfP selected for the previous image IMP (this situation is represented on
As a second variant, the validation criterion is defined according a validation pattern of distribution of the selected reference tone-mapping functions over the different images of the validation sequence. For instance, if the distribution of different selected reference tone-mapping functions P1 and P2 over 20 images forming a validation sequence are: P1P1P1P2P2P1P1P1P2P2P2P1P1P1P2P2P2P2P1P1, as the pattern of distribution of P2 over images shows an increasing weight of P2 compared to that of P1 over the same images, P2 will be validated although the first bin for P1 with a value of 11 is superior to the second bin for P2 with a value of 9.
It may happen that at least one of the reference tone-mapping functions selected for the current validation sequence is the same as the one TMfM that has been validated for the previous validation sequence, i.e. for instance that TMfM=P1. In case this reference tone-mapping function is validated (P1 being the most populated in the distribution), the tone-mapping function applied to images of the current validation sequence remains the same as the reference tone-mapping function applied to images of the previous current validation.
The last step of the current iteration is the application of the validated reference tone-mapping function to images of the current validation sequence, resulting in the following tone-mapped images TMkIMN, TMkIMN+1, . . . , TMkIMk, . . . , TMkIMN+i.
Then, the above selection of a reference tone-mapping function for an image and its application to this image is reiterated for images following last image IMN+i of the validation sequence until a reference tone-mapping function selected for one of these following images is again different from a reference tone-mapping function selected for the previous image, and a new selection is performed again as above for each image of another validation sequence, another validation is performed as above of another reference tone-mapping function for this other validation sequence which is then applied to images of this other validation sequence.
Such iterations are performed until the end of the video content, resulting in a tone-mapped video content.
Thanks to the change the tone-mapping functions only after validation of the selection for several successive images of the content, too frequent changes of tone-mapping functions inside such a video content are prevented, temporal instabilities and visual discomfort are avoided during visualization.
In a preferred variant, when the reference tone-mapping function P2 which is validated for the current validation sequence is different from the reference tone-mapping function P1 validated for the previous validation sequence, a progressive change of tone-mapping function from P1 to P2 is implemented.
This progressive change of tone-mapping function is applied to images of a transition sequence.
The number of images in the transition sequence can for instance be defined as a fixed number, or can be obtained by metadata, or can be an homogeneous non-decreasing function of a difference between the reference tone-mapping function P2 which is validated for the current validation sequence and the reference tone-mapping function P1 validated for the previous validation sequence, the maximum number of images in the transition sequence being the number i of images in the current validation sequence.
It is assumed that a number j of images in the transition sequence is obtained, where j<i. Instead of applying the reference tone-mapping function P2 validated for the current validation sequence to each of the j first images of the current validation sequence, a transition tone-mapping function TMTRt is applied to each IMt of these j images which is obtained by an interpolation between the two validated reference tone-mapping function P1 and P2, preferably according to the formula: TMTRt=t/j*P1+(1−t/j)*P2, where t is the ordering number of this image IMt in the transition sequence. Along images of the transition sequence, the weight of the newly validated reference tone-mapping function P2 is then progressively increased and the weight of the previously validated reference tone-mapping function P1 is then progressively decreased in transition tone-mapping functions TMTRt, with t varying from 1 to j, applied to these images.
Although the illustrative embodiments of the invention have been described herein with reference to the accompanying drawings, it is to be understood that the present invention is not limited to those precise embodiments, and that various changes and modifications may be effected therein by one of ordinary skill in the pertinent art without departing from the invention. All such changes and modifications are intended to be included within the scope of the present invention as set forth in the appended claims. The present invention as claimed therefore includes variations from the particular examples and preferred embodiments described herein, as will be apparent to one of skill in the art.
While some of the specific embodiments may be described and claimed separately, it is understood that the various features of embodiments described and claimed herein may be used in combination. Reference numerals appearing in the claims are by way of illustration only and shall have no limiting effect on the scope of the claims.
Number | Date | Country | Kind |
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18305931 | Jul 2018 | EP | regional |
Filing Document | Filing Date | Country | Kind |
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PCT/US2019/030103 | 5/1/2019 | WO | 00 |
Publishing Document | Publishing Date | Country | Kind |
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WO2020/013904 | 1/16/2020 | WO | A |
Number | Name | Date | Kind |
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9087382 | Zhai | Jul 2015 | B2 |
9336578 | Wang | May 2016 | B2 |
9406112 | Banterle et al. | Aug 2016 | B2 |
10148906 | Seifi | Dec 2018 | B2 |
10176561 | Evans | Jan 2019 | B2 |
10319085 | Min | Jun 2019 | B2 |
10530995 | Douady-Pleven | Jan 2020 | B2 |
10535124 | Guermoud | Jan 2020 | B2 |
10984698 | Shin | Apr 2021 | B2 |
20150348245 | Horiuchi | Dec 2015 | A1 |
20160328830 | Pouli | Nov 2016 | A1 |
20170070719 | Smolic et al. | Mar 2017 | A1 |
20180150946 | Roffet | May 2018 | A1 |
Number | Date | Country |
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3087730 | Nov 2016 | EP |
3249606 | Nov 2017 | EP |
WO 2015096955 | Jul 2015 | WO |
WO 2016192937 | Dec 2016 | WO |
WO 2017032822 | Mar 2017 | WO |
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20210272250 A1 | Sep 2021 | US |