CN103974051A - Image processing device and image processing method - Google Patents
Image processing device and image processing method Download PDFInfo
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- CN103974051A CN103974051A CN201310034081.2A CN201310034081A CN103974051A CN 103974051 A CN103974051 A CN 103974051A CN 201310034081 A CN201310034081 A CN 201310034081A CN 103974051 A CN103974051 A CN 103974051A
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Abstract
The invention provides an image processing device. The image processing device is used for processing multiple pieces of first image data, in a first color space, of an image. The first color space is defined by a plurality of color elements which do not include a saturation element. The image processing device comprises a conversion module, a gain decision module and an adjustment module. The conversion module is used for converting the multiple pieces of first image data into multiple pieces of second image data in a second color space. The second color space is defined by a plurality of second color elements which include the saturation element. The gain decision module is used for deciding the saturation gain according to the part, related to the saturation element, of the multiple pieces of second image data. The adjustment module is used for adjusting the picture according to the saturation gain.
Description
Technical field
The present invention relates to image processing technique relevant, especially relate to image processor and the image treatment method of improving picture saturation.
Background technology
In recent years, flourish along with various electronic products, the multimedia systems such as family's theater are day by day universal.In most multimedia systems, most important hardware unit just belongs to display device.How suitably to adjust the picture that display device presents, to meet beholder's hobby, be the important issue that product producer pays close attention to always.For example, the sharpness that improves image can make the clear of picture change, and the saturation (saturation) that improves image is to make picture color more bright-coloured.
Existing image processing system (for example video camera, Digital Television, DVD player) is to carry out image processing at YCbCr color space mostly.Easy speech, if input signal is the image data representing with rgb color space, this input signal carries out image processing after can being first converted into the image data representing with YCbCr color space again.So in technical field, have and conventionally know known to the knowledgeable, three color element Y, Cb, the Cr of definition YCbCr color space represent respectively brightness, chroma blue and red color, wherein do not comprise saturation.In YCbCr color space, the saturation of a certain image data system represents with the particular kind of relationship of Cb and two color elements of Cr.Therefore, if wish is analyzed the saturation of a certain image in YCbCr color space, must analyze wherein Cb value and the Cr value of each pixel, more particularly, be that Cb value to each pixel and the two-dimensional array of Cr value formation are added up.This routine analyzer needs a large amount of calculation resources (especially in the time that analytic target is high image quality video streaming), and then causes the hardware cost of image processing system to rise.Therefore, current image processing system does not nearly all provide the function of adjusting one by one saturation for each picture in dynamic image.
Summary of the invention
For addressing the above problem, the present invention proposes new image processor and image treatment method, by image data being converted to the color space that its color element comprises a saturation element, in the situation that not needing complex calculation program, can effectively find out the saturation infromation of a picture, and then improve accordingly or reduce the saturation of this picture.
A specific embodiment according to the present invention is a kind of image processor, for processing many first image datas of a picture in one first color space.This first color space system is defined by multiple the first color elements.This image processor comprises a modular converter, gain decision module and an adjusting module.This modular converter is in order to these many first image datas are converted to many second image datas in one second color space.This second color space system is defined by multiple the second color elements, and the plurality of the second color element comprises a saturation element.This gain decision module system is in order to determine a saturation gain according to these many second image data parts relevant to this saturation element.This adjusting module system is in order to adjust this picture according to this saturation gain.
Another specific embodiment according to the present invention is a kind of image treatment method, for processing many first image datas of a picture in one first color space.This first color space system is defined by multiple the first color elements.First this image treatment method carries out a switch process, and these many first image datas are converted to many second image datas in one second color space.This second color space system is defined by multiple the second color elements.The plurality of the second color element comprises a saturation element.Then, this image treatment method is carried out a deciding step, determines a saturation gain according to these many second image data parts relevant to this saturation element.This image treatment method is carried out a set-up procedure subsequently, adjusts this picture according to this saturation gain.
Brief description of the drawings
For above-mentioned purpose of the present invention, feature and advantage can be become apparent, below in conjunction with accompanying drawing, the specific embodiment of the present invention is elaborated, wherein:
Fig. 1 is according to the functional block diagram of the image processor in one embodiment of the invention.
Fig. 2 A ~ Fig. 2 C is in order to present several examples that can impose the object of adjustment programme according to adjusting module of the present invention.
Fig. 3 is according to the functional block diagram of the image treatment method in one embodiment of the invention.
Fig. 4 is a saturation histogram example.
100: image processor 12: modular converter
14: gain decision module 16: adjusting module
S31 ~ S33: process step
Embodiment
Be an image processor according to one embodiment of the invention, its functional block diagram as shown in Figure 1.Image processor 100 comprises modular converter 12, gain decision module 14 and adjusting module 16.In practical application, image processor 100 can be integrated in the various electronic systems with adjustment image saturation demand, also can independently exist.
Modular converter 12 is responsible for changing image data between different color spaces.In the present embodiment, one first color space system is defined by multiple the first color elements, and the plurality of the first color element does not comprise saturation element.Relatively, one second color space system is defined by multiple the second color elements, and the plurality of the second color element comprises saturation element.In an embodiment, the first color space can be rgb color space or YCbCr color space, and the second color space can be HSV color space, HSL color space or HIS color space.Following examples mainly illustrate as HSV color space as example taking the first color space as rgb color space the second color space, but category of the present invention is not as limit.
In this embodiment, the input signal of modular converter 12 is many image datas (hereinafter referred to as RGB image data) of a picture in rgb color space.In practice, provide to a video streaming of image processor 100 and may comprise multiple pictures, wherein comprise this picture of inputting modular converter 12, and multiple pictures that image processor 100 can comprise for this video streaming respectively carry out image processing program.Modular converter 12 is converted to many image datas (hereinafter referred to as HSV image data) of this picture in HSV color space according to following equation by these RGB image datas:
H=max(R,G,B)-min(R,G,B)，
V=max(R,G,B)，
Three color element H, S, the V of definition HSV color space represent respectively form and aspect (hue), saturation (satuation), tone (luminance).That is to say, the output signal of modular converter 12 comprises each image data saturation infromation separately.
Subsequently, in the HSV image data that gain decision module 14 provides according to modular converter 12, the part relevant to saturation element S determines a saturation gain.In an embodiment, gain decision module 14 is made the saturation histogram (histogram) of these HSV image datas, and its transverse axis represents saturation dimension, and the longitudinal axis represents the quantity in this picture with the pixel of a certain saturation.In the saturation histogram example presenting at Fig. 4, the saturation distribution scope after standardization is 1 ~ 32, and is 28 corresponding to the maximum saturation dimension of pixel quantity in this histogram.In an embodiment, gain decision module 14 can be directly by the 28 representative saturations of electing this picture as.In another embodiment, gain decision module 14 can start the pixel quantity corresponding to different saturation to add up by the minimum part of saturation, find out accumulation results with respect to a ratio of total pixel number amount corresponding saturation for example, during higher than a threshold value (percentage 95), as the representative saturation of this picture.
In practice, the mode of calculating saturation gain has a variety of, in an embodiment, saturation gain be set to the saturation upper limit divided by representative saturation (in previous embodiment, 32 divided by 28) result of calculation, in another embodiment, saturation gain is set to representative saturation and is multiplied by the result of calculation after a specific gravity (being for example multiplied by 1.05 or 0.95 by 28).This specific gravity can be selected according to user's preference, also can be before product export default fixed value.
It should be noted that, why no matter produce the mode of saturation gain, due to the saturation infromation that directly comprises each pixel to the HSV image data of gain decision module 14 being provided, gain decision module 14 does not need to carry out complicated statistics and computing, can find out the representative saturation of a picture.In other words,, as long as the definition of the corresponding color space of output signal of modular converter 12 comprises saturation element, gain decision module 14 just can be found out the saturation infromation of picture fast and effectively.Should be noted that in addition, different users's visual experience is different, common also none optimization criteria of saturation height of image.Therefore, which kind of mode is gain decision module 14 can determine to adopt determine this saturation gain according to the rule of thumb.
Then this picture is adjusted in the saturation gain that, adjusting module 16 is responsible for producing according to gain decision module 14.In practice, the object that the module that is adjusted 16 is adjusted can decide according to rear end demand.In an embodiment, as shown in Figure 2 A, adjusting module 16 can directly change the RGB image data of this picture according to this saturation gain, for example, these RGB image datas are multiplied by respectively to this saturation gain.In another embodiment, as shown in Figure 2 B, adjusting module 16 can change according to this saturation gain the HSV image data of this picture, for example, each saturation element S in these HSV image datas is multiplied by respectively to this saturation gain.If image processor 100 need provide to the output signal form of back-end circuit be RGB data, these through change after HSV image datas can again be converted back to RGB image data.
In another embodiment, as shown in Figure 2 C, modular converter 12 is also converted to the RGB image data of a picture for example, many 3rd image datas in another third color space (YCbCr color space), and adjusting module 16 is, according to this saturation gain, these many 3rd image datas are multiplied by respectively to this saturation gain, to reach the effect of adjusting this picture.If third color space is YCbCr color space, adjusting module 16 can be multiplied by respectively this saturation gain by the Cb value of each image data and Cr value, and does not adjust its Y value.The benefit of this way be the brightness of this picture can not be subject to saturation change impact and with variation.
In practice, the saturation gain that adjusting module 16 can be directly provide using gain decision module 14 is as the product of adjusting each image data, also can be in addition finds out according to look-up table or certain operations formula the product gaining corresponding to this saturation and adjusts image data.
Be an image treatment method according to another embodiment of the present invention, its flow chart as shown in Figure 3.This image treatment method system is for processing many first image datas of a picture in one first color space.This first color space system is defined by multiple the first color elements, and the plurality of the first color element does not comprise a saturation element.This second color space system is defined by multiple the second color elements, and the plurality of the second color element comprises this saturation element.First this image treatment method performs step S31, and these many first image datas are converted to many second image datas in one second color space.Then, this image treatment method execution step S32, determines a saturation gain according to these many second image data parts relevant to this saturation element.This image treatment method performs step S33 subsequently, adjusts this picture according to this saturation gain.
The various circuit operations of previously having described in the time introducing image processor 100 change (mode that for example determines saturation gain) and also can be applied in the image treatment method that Fig. 3 illustrates, and its details repeats no more.
As mentioned above, the present invention proposes new image processor and image treatment method, by image data being converted to the color space that its color element comprises a saturation element, in the situation that not needing complex calculation program, can effectively find out the saturation infromation of a picture, and then improve accordingly or reduce the saturation of this picture.Device and method according to the present invention for example can be applicable to, in the various electronic systems (video camera, Digital Television, DVD player) with adjustment image saturation demand, and its range of application comprises dynamic image and static image.
Although the present invention discloses as above with preferred embodiment; so it is not in order to limit the present invention, any those skilled in the art, without departing from the spirit and scope of the present invention; when doing a little amendment and perfect, therefore protection scope of the present invention is worked as with being as the criterion that claims were defined.
Claims (20)
1. an image processor, for processing many first image datas of a picture in one first color space, this first color space is to be defined by multiple the first color elements, this image processor comprises:
One modular converter, in order to these many first image datas are converted to many second image datas in one second color space, this second color space is to be defined by multiple the second color elements, the plurality of the second color element comprises a saturation element;
One gain decision module, in order to determine a saturation gain according to these many second image data parts relevant to this saturation element; And
One adjusting module, in order to adjust this picture according to this saturation gain.
2. image processor as claimed in claim 1, is characterized in that, this first color space is a rgb color space or a YCbCr color space.
3. image processor as claimed in claim 1, is characterized in that, this second color space is a HSV color space, a HSL color space or a HIS color space.
4. image processor as claimed in claim 1, it is characterized in that, this gain decision module is made a saturation histogram of these many second image datas to find out a representative saturation of this picture, and determines this saturation gain according to this representativeness saturation.
5. image processor as claimed in claim 4, it is characterized in that, these many second image datas are corresponding to a total pixel number amount, this gain decision module from a minimum saturation of this saturation histogram to high saturation accumulative total one pixel quantity, when this pixel quantity with respect to a ratio of this total pixel number amount higher than a threshold value, this gain decision module is using corresponding this saturation of this pixel quantity as this representativeness saturation.
6. image processor as claimed in claim 1, is characterized in that, these many first image datas are multiplied by respectively this saturation gain by this adjusting module, to adjust this picture.
7. image processor as claimed in claim 1, is characterized in that, these many second image datas this saturation element is separately multiplied by respectively this saturation gain by this adjusting module, to adjust this picture.
8. image processor as claimed in claim 1, it is characterized in that, this modular converter is more converted to these many first image datas many 3rd image datas in one third color space, and these many 3rd image datas are multiplied by respectively the gain of this saturation by this adjusting module, to adjust this picture.
9. image processor as claimed in claim 8, it is characterized in that, this first color space is a rgb color space, this second color space is a HSV color space, this third color space is a YCbCr color space, and this adjusting module is that these many 3rd image datas Cb value and Cr value is separately multiplied by respectively to this saturation gain, to adjust this picture.
10. image processor as claimed in claim 1, is characterized in that, this picture is contained in to be provided to a video streaming of this image processor, and this image processor is adjusted multiple pictures that this video streaming comprises.
11. 1 kinds of image treatment methods, for processing many first image datas of a picture in one first color space, this first color space is to be defined by multiple the first color elements, this image treatment method comprises:
(a) these many first image datas are converted to many second image datas in one second color space, this second color space is to be defined by multiple the second color elements, and the plurality of the second color element comprises a saturation element;
(b) determine a saturation gain according to these many second image data parts relevant to this saturation element; And
(c) adjust this picture according to this saturation gain.
12. image treatment methods as claimed in claim 11, is characterized in that, this first color space is a rgb color space or a YCbCr color space.
13. image treatment methods as claimed in claim 11, is characterized in that, this second color space is a HSV color space, a HSL color space or a HIS color space.
14. image treatment methods as claimed in claim 11, is characterized in that, step (b) comprises:
(b1) saturation histogram of making these many second image datas is to find out a representative saturation of this picture; And
(b2) determine this saturation gain according to this representativeness saturation.
15. image treatment methods as claimed in claim 14, is characterized in that, these many second image datas are corresponding to a total pixel number amount, and step (b1) comprises:
From a minimum saturation of this saturation histogram to high saturation accumulative total one pixel quantity; And
When this pixel quantity after accumulative total with respect to a ratio of this total pixel number amount higher than a threshold value, using corresponding this saturation of this pixel quantity as this representativeness saturation.
16. image treatment methods as claimed in claim 11, is characterized in that, step (c) comprises these many first image datas are multiplied by respectively to the gain of this saturation, to adjust this picture.
17. image treatment methods as claimed in claim 11, is characterized in that, step (c) comprises these many second image datas this saturation element is separately multiplied by respectively to the gain of this saturation, to adjust this picture.
18. image treatment methods as claimed in claim 11, further comprise:
These many first image datas are converted to many 3rd image datas in a third color space;
Wherein step (c) comprises these many 3rd image datas is multiplied by respectively to the gain of this saturation, to adjust this picture.
19. image treatment methods as claimed in claim 18, it is characterized in that, this first color space is a rgb color space, this second color space is a HSV color space, this third color space is a YCbCr color space, and step (c) comprises Cb value separately of these many 3rd image datas and Cr value is multiplied by respectively to this saturation gain, to adjust this picture.
20. image treatment methods as claimed in claim 11, is characterized in that, this picture is to be contained in a video streaming, and this image treatment method is used to adjust multiple pictures that this video streaming comprises.
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| CN106373517A (en) * | 2016-10-31 | 2017-02-01 | 北京集创北方科技股份有限公司 | Display and display method |
| CN106998456A (en) * | 2017-03-28 | 2017-08-01 | 建荣半导体（深圳）有限公司 | A kind of method of adjustment, device and the picture processing chip of image color saturation |
| WO2020118926A1 (en) * | 2018-12-11 | 2020-06-18 | 惠科股份有限公司 | Display panel driving method, driving system, and display device |
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Cited By (6)
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| CN105225647A (en) * | 2015-10-15 | 2016-01-06 | 小米科技有限责任公司 | Luminance regulating method and device |
| CN105225647B (en) * | 2015-10-15 | 2018-09-18 | 小米科技有限责任公司 | Luminance regulating method and device |
| CN106373517A (en) * | 2016-10-31 | 2017-02-01 | 北京集创北方科技股份有限公司 | Display and display method |
| CN106998456A (en) * | 2017-03-28 | 2017-08-01 | 建荣半导体（深圳）有限公司 | A kind of method of adjustment, device and the picture processing chip of image color saturation |
| WO2020118926A1 (en) * | 2018-12-11 | 2020-06-18 | 惠科股份有限公司 | Display panel driving method, driving system, and display device |
| US11355078B2 (en) | 2018-12-11 | 2022-06-07 | HKC Corporation Limited | Display panel driving method, driving system and display device |
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Application publication date: 20140806 |