CN102768758A - Improved color image unsharp masking (USM) method - Google Patents
Improved color image unsharp masking (USM) method Download PDFInfo
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- CN102768758A CN102768758A CN2012102280648A CN201210228064A CN102768758A CN 102768758 A CN102768758 A CN 102768758A CN 2012102280648 A CN2012102280648 A CN 2012102280648A CN 201210228064 A CN201210228064 A CN 201210228064A CN 102768758 A CN102768758 A CN 102768758A
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- 238000000034 method Methods 0.000 title claims abstract description 43
- 230000000873 masking effect Effects 0.000 title abstract description 3
- 239000000284 extract Substances 0.000 description 8
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- 238000003707 image sharpening Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
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Abstract
The invention discloses an improved color image unsharp masking (USM) method, which comprises the following step of: overlaying an original image of each color channel of a color image on an edge gain to form an image of the color channel after the original image is sharpened, wherein each edge gain is taken from the color image or an image of the color channel with the richest hierarchy in a part serving as an important processing part of the color image. The color image processed by the method is relatively high in edge contrast and relatively clear.
Description
Technical field
The present invention relates to a kind of computer processing method of coloured image, be specifically related to a kind of the improved method of traditional U SM treatment technology.
Background technology
The human information of transmitting has 70 % must pass through vision, and image is the important medium and the means of transmission information.Owing to reasons such as the influence of the restriction of dynamic range, illumination, image displays; Image quality in acquisition process can descend; Make that a lot of information in the original image can not be discerned by human eye, this just need utilize image enhancement technique, makes these information be convenient to human eye identification.
Image sharpening is a kind of in the figure image intensifying, is to utilize various mathematical methods and shift means to improve the contrast and the sharpness of image, with outstanding people or the interested part of other receiving systems.USM sharpening (Unsharp masking) is a kind of disposal route that comes from the traditional photography technology, through extracting image edge information, produces more black and whiter " edging " at the image outline place, thereby improves the visual sharpness of image.In order to improve image definition; What adopt usually is the method for vignette masking-out; Promptly be before the construction drawing picture; Obtain earlier a negative fuzzyyer than original image consciously, cover the photograph of being in step with to this fuzzy image as masking-out and original copy picture then, the result makes the image that obtains than not using masking-out more clear.Also be used in the modern computer image processing techniques in a principle.For discrete digital picture, typical USM method can reduce following formula:
（2）
When carrying out image sharpening with this traditional method, handle the image of each Color Channel of back and all be made up of edge gain of original image stack of passage, this edge gain is extracted from this channel image.
The image sharpening method of above-mentioned routine all uses identical method to handle to each Color Channel; Though can reach the purpose that makes clear picture; But can not play good sharpen effect to some image; As for being master's image with a certain tone, or when being the emphasis of processing with the part of image.Unbalanced situation can appear in each Color Channel level contrast of these images, and some often passage level contrasts are bigger, and rest channels then shows to such an extent that level is comparatively smooth.Its image detail of the diverse passage of level is more, and the edge contrast is also bigger, and the amount of edge of therefrom extracting is more; And for the little passage of differential variation, the amount of edge of therefrom obtaining then seldom.If this type of image is handled by conventional USM sharpening method, the edge that can make level change little passage strengthens very faint, causes the sharpen effect of coloured image not ideal enough.
Summary of the invention
To the objective of the invention is the defective that exists in the prior art in order solving, a kind of higher improved method of coloured image readability that makes to be provided.
In order to achieve the above object, the invention provides a kind of improved coloured image USM sharpening method, this method is formed edge gain of the original image of each Color Channel of coloured image stack the image of this Color Channel after the sharpening; The gain of each edge is all taken from the coloured image or as the image of the local middle-level the abundantest Color Channel of Color Image Processing emphasis.
The formula of above-mentioned USM sharpening method is following:
In the formula (3);
is the original image of single Color Channel;
is the image of this Color Channel after the sharpening;
is in the said coloured image or as the original image of the local middle-level the abundantest Color Channel of said Color Image Processing emphasis;
for the abundantest Color Channel of this level being carried out the image after the Fuzzy Processing,
is the edge gain term of the abundantest Color Channel of this level.
Wherein, coloured image is for adopting the coloured image of rgb color pattern or cmyk color pattern.
The present invention compares prior art and has the following advantages: the edge gain through the Color Channel that level is the abundantest is added in each passage; Make the edge gain of the passage that level is more smooth all be taken from the bigger passage of another one contrast; Therefore can obtain bigger edge strengthens; And the edge of the bigger passage of this contrast strengthen also can with adopt existing USM sharpening method to strengthen the back to maintain an equal level, synthetic thus coloured image profile contrast is bigger, more clear.
Description of drawings
Fig. 1 is each passage gray-scale map of certain RGB image, and wherein, R1 is a R passage gray-scale map, and G1 is a G passage gray-scale map, and B1 is a B passage gray-scale map;
Fig. 2 is the image behind each passage extraction edge among Fig. 1, and wherein, R2 is the outline map that the R passage extracts, and G2 is the outline map that the G passage extracts, and B2 is the outline map that the B passage extracts;
Fig. 3 handles the comparison diagram behind the RGM image among Fig. 1 for adopting traditional USM sharpening method and USM sharpening method of the present invention, and wherein, a is the image after traditional USM sharpening method is handled, and b is the image after USM sharpening method of the present invention is handled;
Fig. 4 is C, M, the Y channel image of certain CMYK image, and wherein, C1 is the C-channel gray-scale map, and M1 is a M passage gray-scale map, and Y1 is a Y passage gray-scale map;
Fig. 5 is the image that each passage extracts the edge among Fig. 4, and wherein, C2 is the outline map that C-channel extracts, the outline map that M2 extracts for the M passage, the outline map that Y2 extracts for the Y passage;
Fig. 6 handles the comparison diagram behind the CMYK image among Fig. 4 for adopting traditional USM sharpening method and USM sharpening method of the present invention, and wherein, c is the image after traditional USM sharpening method is handled, and d is the image after USM sharpening method of the present invention is handled.
Embodiment
Below in conjunction with accompanying drawing the improved coloured image USM of the present invention sharpening method is elaborated.
Embodiment one
RGB image with shown in Figure 1 is an example, in Matlab, it is carried out sharpening and handles.Can find out that by Fig. 2 G channel image level changes obviously in this RGB image, the edge that therefrom extracts is maximum.To take from the edge gain term of the edge gain term of G channel image, and adopt following formula to handle as R, G, three passages of B:
In the formula (4), A takes from the abundantest passage of level, is the G passage.
Adopt traditional sharpening method of formula (2) simultaneously, use identical smooth template in two kinds of methods, identical gain coefficient is handled image.
Can find out that by Fig. 3 adopt the image comparison after this method is handled to adopt the image after traditional sharpening method is handled, the sharpness of image is higher.
Embodiment two
CMYK image with shown in Figure 4 is an example, with fruit is to handle emphasis, in Matlab, it is carried out sharpening and handles.Can find out at the fruit part M of image channel image edge maximum by Fig. 5.To take from the edge gain term of the edge gain term of M channel image as C, M, three passages of Y, employing formula (3) is handled.
Adopt traditional sharpening method of formula (1) simultaneously, use identical smooth template in two kinds of methods, identical gain coefficient is handled image.
Can find out that by Fig. 6 adopt the image comparison after this method is handled to adopt the image after traditional sharpening method is handled, the sharpness of image is higher.
Claims (4)
1. improved coloured image USM sharpening method, said USM sharpening method are formed edge gain of original image stack of each Color Channel of said coloured image the image of this Color Channel after the sharpening; It is characterized in that: the gain of said edge is taken from the said coloured image or as the image of the local middle-level the abundantest Color Channel of said Color Image Processing emphasis.
2. improved coloured image USM sharpening method according to claim 1, it is characterized in that: the formula of said USM sharpening method is following:
; In the formula;
is the original image of single Color Channel;
is the image of this Color Channel after the sharpening;
is in the said coloured image or as the original image of the local middle-level the abundantest Color Channel of said Color Image Processing emphasis;
for the abundantest Color Channel of this level being carried out the image after the Fuzzy Processing,
is the edge gain term of the abundantest Color Channel of this level.
3. improved coloured image USM sharpening method according to claim 1 and 2 is characterized in that: said coloured image is for adopting the coloured image of rgb color pattern.
4. improved coloured image USM sharpening method according to claim 1 and 2 is characterized in that: said coloured image is for adopting the coloured image of cmyk color pattern.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103873839A (en) * | 2012-12-13 | 2014-06-18 | 联咏科技股份有限公司 | Image processing apparatus and method thereof |
| CN104052904A (en) * | 2014-05-28 | 2014-09-17 | 刘远明 | Method and device for image processing of multiresolution upsharp masking (USM) |
| CN108428215A (en) * | 2017-02-15 | 2018-08-21 | 阿里巴巴集团控股有限公司 | A kind of image processing method, device and equipment |
| CN108810397A (en) * | 2018-04-23 | 2018-11-13 | 深圳和而泰数据资源与云技术有限公司 | A kind of image color misregistration correction method and terminal device |
| CN114627030A (en) * | 2022-05-13 | 2022-06-14 | 深圳深知未来智能有限公司 | Self-adaptive image sharpening method and system |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103873839A (en) * | 2012-12-13 | 2014-06-18 | 联咏科技股份有限公司 | Image processing apparatus and method thereof |
| CN104052904A (en) * | 2014-05-28 | 2014-09-17 | 刘远明 | Method and device for image processing of multiresolution upsharp masking (USM) |
| CN108428215A (en) * | 2017-02-15 | 2018-08-21 | 阿里巴巴集团控股有限公司 | A kind of image processing method, device and equipment |
| CN108810397A (en) * | 2018-04-23 | 2018-11-13 | 深圳和而泰数据资源与云技术有限公司 | A kind of image color misregistration correction method and terminal device |
| CN114627030A (en) * | 2022-05-13 | 2022-06-14 | 深圳深知未来智能有限公司 | Self-adaptive image sharpening method and system |
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