CN102646269B - A kind of image processing method of laplacian pyramid and device thereof - Google Patents

A kind of image processing method of laplacian pyramid and device thereof Download PDF

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CN102646269B
CN102646269B CN201210049320.7A CN201210049320A CN102646269B CN 102646269 B CN102646269 B CN 102646269B CN 201210049320 A CN201210049320 A CN 201210049320A CN 102646269 B CN102646269 B CN 102646269B
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林格
林谋广
李彦
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Sun Yat Sen University
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Abstract

The embodiment of the invention discloses a kind of image processing method based on laplacian pyramid and device thereof, wherein, the method comprises: the gaussian pyramid that structure input picture is corresponding; Mediation image is generated according to gaussian pyramid and mapping function r (x); Corresponding Laplce Laplace pyramid coefficient is obtained according to mediation image; Laplace pyramid coefficient based on mediation image is outputted on Laplace pyramid accordingly, until Laplace each point pyramidal is filled, obtains new Laplace pyramid; According to new Laplace Pyramid Reconstruction image, and obtain output image.Implement the embodiment of the present invention, the constraint that traditional Laplace pyramid can not carry out edge maintenance image enhaucament can be broken away from, utilizing Laplace pyramid to carry out edge keeps image to increase process, can than traditional edge keep image increase method (as bilateral filtering, wavelet method etc.) simpler, realize image enhaucament more neatly, can time complexity be reduced, not need to arrange extra mistake multiparameter simultaneously.

Description

A kind of image processing method of laplacian pyramid and device thereof
Technical field
The present invention relates to technical field of image processing, particularly relate to a kind of image processing method and device thereof of laplacian pyramid.
Background technology
Image enhaucament is an important application of computer technology, its objective is and improve the visual effect of people to image, generalized case is the application scenario for Given Graph picture, on purpose emphasize entirety or the local characteristics of image, original unsharp image is become clear or emphasizes some interested feature, difference in expanded view picture between different objects feature, suppress uninterested feature, reach the object improving picture quality, abundant information amount, strengthen image interpretation and recognition effect, meet the needs of some special analysis.
The method of image enhaucament can be divided into two large classes: frequency domain method and space domain method.Algorithm based on frequency domain in certain transform domain of image, carries out certain to the transform coefficient values of image revise, and is a kind of algorithm of indirect enhancing; Directly computing is done to image gray levels during algorithm process based on spatial domain.The former regards a kind of 2D signal as image, carries out strengthening based on the signal of two-dimensional Fourier transform to it.Adopt low-pass filtering (namely only allowing low frequency signal pass through) method, the noise in figure can be removed; Adopt high-pass filtering method, then can strengthen the high-frequency signals such as edge, make fuzzy picture become clear.The latter is divided into point processing algorithm and neighborhood denoise algorithm based on the algorithm in spatial domain.Point processing algorithm and gray level correction, greyscale transformation and histogram modification etc., object makes image imagewise uniform, or expand dynamic range of images, expanded contrast.Neighborhood strengthens algorithm and is divided into image smoothing and sharpening two kinds.Smoothly be generally used for removal of images noise, but also easily cause the fuzzy of edge.Algorithms most in use has mean filter, medium filtering.The object of sharpening is the edge contour of outstanding object, is convenient to target identification.Algorithms most in use has gradient method, operator, high-pass filtering, mask matching method, statistics differential technique etc.
In prior art, although many methods can use in image boundary, such as two-sided filter method, wavelet method etc.Bilateral filtering is a kind of wave filter can protecting limit denoising, and can reach this denoising effect is because wave filter is made up of two functions, and a function determines filter coefficient by geometric space distance, and another determines filter coefficient by pixel value difference; Wavelet method is with some special function for data procedures or DS are transformed to progression series to find the feature of its similar frequency spectrum by base, thus realizes data processing.But these methods all compare in processes and expend time in, and limit its practical ranges because of problems such as needs pre-treatment, quantity of parameters are arranged.
Summary of the invention
The object of the invention is to overcome the deficiencies in the prior art, the invention provides a kind of image processing method and device thereof of laplacian pyramid, the constraint that traditional Laplace pyramid can not carry out edge maintenance image enhaucament can be broken away from, more simply, more neatly can realize image enhaucament.
In order to solve the problem, the present invention proposes a kind of image processing method based on laplacian pyramid, described method comprises:
The gaussian pyramid that structure input picture is corresponding;
Mediation image is generated according to described gaussian pyramid and mapping function r (x);
Corresponding Laplce Laplace pyramid coefficient is obtained according to described mediation image;
Laplace pyramid coefficient based on described mediation image is outputted on Laplace pyramid accordingly, until described Laplace each point pyramidal is filled, obtains new Laplace pyramid;
According to described new Laplace Pyramid Reconstruction image, and obtain output image.
Preferably, the described step generating mediation image according to described gaussian pyramid and mapping function r (x) comprises: according to described gaussian pyramid and
r ( i ) = g 0 + sign ( i - g 0 ) σ r f d ( i a ) , | i - g 0 | ≤ σ g 0 + sign ( i - g 0 ) [ f e ( | i - g 0 | - σ r ) + σ r ] , otherwise
Generate mediation image;
Wherein, parameter σ rthe threshold values for distinguishing border and texture, g 0the expectation pixel value of this point of surface, function f dand f eby the smooth function of [0,1] Interval Maps to [0,1] interval, f drepresent details enhancing function, f erepresent hue enhancement function, i is the original pixel value of this point, | i-g 0| be the grey scale change in this field, a changes the degree strengthened adjustment details.
Preferably, the described step generating mediation image according to described gaussian pyramid and mapping function r (x) comprises:
Detail signal process is carried out to described input picture and the margin signal of described input picture is compressed.
Preferably, the step of the gaussian pyramid that described structure input picture is corresponding comprises:
Construct the gaussian pyramid that the image I of size w × h is corresponding, wherein, gaussian pyramid G ithe Gaussian image I reduced by the resolution of I icomposition, i represents the progression of gaussian pyramid, i={0, and 1 ..., j}, image I isize be (w/2 i) × (h/2 i).
Preferably, in described gaussian pyramid, every one deck pyramid diagram picture to be reduced by half generation by the wide and height of lower one deck pyramid diagram picture.
Correspondingly, the embodiment of the present invention also provides a kind of image processing apparatus based on laplacian pyramid, and described image processing apparatus comprises:
Constructing module, for constructing the corresponding gaussian pyramid of input picture;
Generation module, generates mediation image for the gaussian pyramid that constructs according to described constructing module and mapping function r (x);
Coefficient obtains module, and the mediation image for generating according to described generation module obtains corresponding Laplce Laplace pyramid coefficient;
Laplacian pyramid generation module, for the Laplace pyramid coefficient based on described mediation image is outputted to Laplace pyramid accordingly, until described Laplace each point pyramidal is filled, obtains new Laplace pyramid;
Image Reconstruction module, for the new Laplace Pyramid Reconstruction image generated according to described laplacian pyramid generation module, and obtains output image.
Preferably, described generation module also for according to described gaussian pyramid and
r ( i ) = g 0 + sign ( i - g 0 ) σ r f d ( i a ) , | i - g 0 | ≤ σ g 0 + sign ( i - g 0 ) [ f e ( | i - g 0 | - σ r ) + σ r ] , otherwise
Generate mediation image;
Wherein, parameter σ rthe threshold values for distinguishing border and texture, g 0the expectation pixel value of this point of surface, function f dand f eby the smooth function of [0,1] Interval Maps to [0,1] interval, f drepresent details enhancing function, f erepresent hue enhancement function, i is the original pixel value of this point, | i-g 0| be the grey scale change in this field, a changes the degree strengthened adjustment details.
Preferably, described generation module is also for carrying out detail signal process and compressing the margin signal of described input picture to described input picture.
Preferably, described constructing module also for the gaussian pyramid that the image I constructing size w × h is corresponding, wherein, gaussian pyramid G ithe Gaussian image I reduced by the resolution of I icomposition, i represents the progression of gaussian pyramid, i={0, and 1 ..., j}, image I isize be (w/2 i) × (h/2 i).
Preferably, in described gaussian pyramid, every one deck pyramid diagram picture to be reduced by half generation by the wide and height of lower one deck pyramid diagram picture.
Implement the method for the embodiment of the present invention, the constraint that traditional Laplace pyramid can not carry out edge maintenance image enhaucament can be broken away from, utilizing Laplace pyramid to carry out edge keeps image to increase process, can than traditional edge keep image increase method (as bilateral filtering, wavelet method etc.) simpler, realize image enhaucament more neatly, can time complexity be reduced, not need to arrange extra mistake multiparameter simultaneously.
Accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.
Fig. 1 is the schematic flow sheet of the image processing method based on laplacian pyramid of inventive embodiments;
Fig. 2 is the signal composition schematic diagram of one dimensional image in the embodiment of the present invention;
Fig. 3 is the one-dimensional signal composition schematic diagram of the image using laplacian pyramid mode to construct in the embodiment of the present invention;
Fig. 4 is the principle of work schematic diagram of the luminance compression of the embodiment of the present invention;
Fig. 5 is the structure composition schematic diagram of the image processing apparatus based on laplacian pyramid of the embodiment of the present invention.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, be clearly and completely described the technical scheme in the embodiment of the present invention, obviously, described embodiment is only the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.
The present invention does edge based on Laplce (Laplace) pyramid to keep image enhaucament, and therefore Laplace pyramid is its core content, and Laplace pyramid is based on gaussian pyramid (Gaussian Pyramid).In Gaussian pyramid, the bottom is its original image, i.e. G 0=I, and wide and high the reducing by half that every one deck pyramid diagram picture is all lower one deck pyramid diagram picture generates.And traditional Laplace pyramid is undertaken expanding and the error image of next tomographic image by interpolation by last layer image, its reflection be the information gap of gaussian pyramid two inter-stage, i.e. details.
The embodiment of the present invention provides a kind of image processing method based on laplacian pyramid, and Fig. 1 is the schematic flow sheet of the image processing method based on laplacian pyramid of inventive embodiments, and as shown in Figure 1, the method comprises:
S101, the gaussian pyramid that structure input picture is corresponding;
S102, the gaussian pyramid corresponding according to input picture and mapping function r (x) generate mediation image;
S103, obtains corresponding Laplce Laplace pyramid coefficient according to mediation image;
S104, outputs on Laplace pyramid accordingly by the Laplace pyramid coefficient based on mediation image, until Laplace each point pyramidal is filled, obtains new Laplace pyramid;
S105, according to new Laplace Pyramid Reconstruction image, and obtains output image.
In concrete enforcement, be the image I of w × h for size, in S101, the gaussian pyramid that the image I of size w × h is corresponding can be constructed, wherein, gaussian pyramid G ithe Gaussian image I reduced by the resolution of I icomposition, i represents the progression of gaussian pyramid, i={0, and 1 ..., j}, image I isize be (w/2 i) × (h/2 i).
Wherein, 102 comprise further: according to gaussian pyramid and
r ( i ) = g 0 + sign ( i - g 0 ) σ r f d ( i a ) , | i - g 0 | ≤ σ g 0 + sign ( i - g 0 ) [ f e ( | i - g 0 | - σ r ) + σ r ] , otherwise
Generate mediation image;
Wherein, parameter σ rthe threshold values for distinguishing border and texture, g 0be the expectation pixel value of this point of surface, function f is by the smooth function of [0,1] Interval Maps to [0,1] interval, f drepresent details enhancing function, f erepresent hue enhancement function, i is the original pixel value of this point, | i-g 0| be the grey scale change in this field, a changes the degree strengthened adjustment details.
About mapping function r, wherein, input parameter σ rthe threshold values for distinguishing border and texture, namely when the grey scale change in certain vertex neighborhood is less than or equal to σ rtime, then think texture, when being greater than σ rshi Ze thinks border.And g 0it is then the expectation pixel value of this point of surface.When the some variation range in neighborhood is all not more than the threshold value on border, can think that this point is in texture region; Otherwise, then show near border.For these two kinds different situations, the form of mapping function r is different.But without argument in what region, mapping function r should be monotonically increasing, to ensure the situation that there will not be gray scale to reverse.Further, in order to ensure the continuity of gradation of image, no matter which region the point being positioned at threshold value place is in, the functional value after their mappings should be equal.
In concrete enforcement, when generating mediation image, on the one hand detail signal process being carried out to input picture, on the other hand the margin signal of input picture being compressed, namely will block original signal this pixel value and g in certain neighborhood 0difference in codomain is greater than σ rvalue.
In specific implementation process, said method process can be applied to color space, only r and g in above formula need be changed to vector, absolute value changes vector norm into, and sign function changes following unitization function into.
unit ( v → ) = v → | | v → | |
In image processing process, be all generally first analyze one dimensional image, then expand to the analysis to coloured image.
When analyzing signal (one-dimensional signal) of one dimensional image, first analyze the composition of one-dimensional signal, one-dimensional signal I is made up of three parts, margin signal E, change slow signal S, high-frequency signal D, specifically as shown in Figure 2, margin signal E is typical step function, and the average of high-frequency signal D is zero, and the gradient magnitude on every bit all will much smaller than ladder amplitude of variation in E.Change the low frequency component in slow signal S representation signal, the slow increase of such as signal intensity or minimizing.For the regional area of image, the every bit in signal can be expressed as the linear combination of above-mentioned 3 signals, and just different local, the coefficient of each component is not identical.
When the pyramidal mode of use Laplace constructs ground floor L 0, second layer L 1, third layer L 2deng, in whole Laplace pyramid, the situation of one-dimensional signal as shown in Figure 3, can be drawn by Fig. 3:
(1) pyramidal progression is higher, and high frequency detail just fades away;
(2) pyramidal progression is higher, and picture size is more and more less, and the change frequency of otherwise smooth can raise, and produces high-frequency signal;
(3) composition does not reduce along with the raising of level, and this illustrates that border still can be determined in the figure of low resolution.
Can find out that laplace coefficient can be taken as from analysis content is above details or edge, and edge amplitude is far longer than the amplitude of details, therefore can pass through parameter σ rdistinguish border and texture.
The method of the embodiment of the present invention can be applied in the image enhaucament aspects such as details enhancing, tone mapping, needs to arrange different parameters in concrete application process.In tone mapping, the method for luminance compression can be adopted.Luminance compression can realize D+E → D+E ', and wherein D is detail signal, and E is margin signal, and E ' is the margin signal after change, namely same detail section, and marginal portion reduces, and is that margin signal is compressed, margin signal is changed in concrete enforcement.As shown in Figure 4, as shown in Figure 4, the signal after process is compared with original signal, and the amplitude of margin signal decreases, but owing to not changing detail signal, therefore the character of signal remains unchanged for the principle of work of luminance compression.
Luminance compression specific operation process is: output signal is set to I ', the image sequence that its each layer of Laplace image pyramid forms then is designated as L [I '] }.By L [I '] } can be easy to rebuild back output signal.The pixel value of any in { L [I '] } on a certain image, by the position x of pixel 0l is determined with image place layer 0(L 0the bottom of laplacian pyramid, namely gaussian pyramid ground floor and the second layer double after difference obtain).The pixel value of same layer same point in Gaussian image pyramid is set to g 0.The intermediary layer Laplace pyramid constructed in method described in the embodiment of the present invention will block original signal this pixel value and g in certain neighborhood 0distance in codomain is greater than σ rvalue, namely have
T=min [max (I, g 0-σ r), g 0+ σ r], the tone mapping of image can be realized by above-mentioned luminance compression method.
Implement the method for the embodiment of the present invention, the constraint that traditional Laplace pyramid can not carry out edge maintenance image enhaucament can be broken away from, utilizing Laplace pyramid to carry out edge keeps image to increase process, can than traditional edge keep image increase method (as bilateral filtering, wavelet method etc.) simpler, realize image enhaucament more neatly, can time complexity be reduced, not need to arrange extra mistake multiparameter simultaneously.
The embodiment of the present invention additionally provides a kind of image processing apparatus based on laplacian pyramid, and Fig. 5 is the structure composition schematic diagram of the image processing apparatus based on laplacian pyramid of the embodiment of the present invention, and as shown in Figure 5, this image processing apparatus comprises:
Constructing module 50, for constructing the corresponding gaussian pyramid of input picture;
Generation module 51, generates mediation image for the gaussian pyramid that constructs according to constructing module 50 and mapping function r (x);
Coefficient obtains module 52, and the mediation image for generating according to generation module 51 obtains corresponding Laplce Laplace pyramid coefficient;
Laplacian pyramid generation module 53, for the Laplace pyramid coefficient based on mediation image is outputted to Laplace pyramid accordingly, until Laplace each point pyramidal is filled, obtains new Laplace pyramid;
Image Reconstruction module 54, for the new Laplace Pyramid Reconstruction image generated according to laplacian pyramid generation module, and obtains output image.
In concrete enforcement, in concrete enforcement, be the image I of w × h for size, the corresponding gaussian pyramid of the image I of size w × h can be constructed by constructing module 50, wherein, gaussian pyramid G ithe Gaussian image I reduced by the resolution of I icomposition, i represents the progression of gaussian pyramid, i={0, and 1 ..., j}, image I isize be (w/2 i) × (h/2 i).Wherein, generation module 51 also for according to gaussian pyramid and
r ( i ) = g 0 + sign ( i - g 0 ) σ r f d ( i a ) , | i - g 0 | ≤ σ g 0 + sign ( i - g 0 ) [ f e ( | i - g 0 | - σ r ) + σ r ] , otherwise
Generate mediation image;
Wherein, parameter σ rthe threshold values for distinguishing border and texture, g 0be the expectation pixel value of this point of surface, function f is by the smooth function of [0,1] Interval Maps to [0,1] interval, f drepresent details enhancing function, f erepresent hue enhancement function, i is the original pixel value of this point, | i-g 0| be the grey scale change in this field, a changes the degree strengthened adjustment details.
Generation module 51 is also for carrying out detail signal process and compressing the margin signal of input picture to input picture.
The implementation procedure of each functions of modules of the image processing apparatus based on laplacian pyramid in apparatus of the present invention embodiment and principle can describe see the respective process in the embodiment of the image processing method based on laplacian pyramid of the present invention, repeat no more here.
In apparatus of the present invention embodiment, utilizing Laplace pyramid to carry out edge keeps image to increase process, the constraint that traditional Laplace pyramid can not carry out edge maintenance image enhaucament can be broken away from, can than traditional edge keep image increase method (as bilateral filtering, wavelet method etc.) simpler, realize image enhaucament more neatly, can time complexity be reduced, not need to arrange extra mistake multiparameter simultaneously.
One of ordinary skill in the art will appreciate that all or part of step in the various methods of above-described embodiment is that the hardware that can carry out instruction relevant by program has come, this program can be stored in a computer-readable recording medium, storage medium can comprise: ROM (read-only memory) (Read Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or CD etc.
In addition, above the image processing method of the laplacian pyramid that the embodiment of the present invention provides and device thereof and device thereof are described in detail, apply specific case herein to set forth principle of the present invention and embodiment, the explanation of above embodiment just understands method of the present invention and core concept thereof for helping; Meanwhile, for one of ordinary skill in the art, according to thought of the present invention, all will change in specific embodiments and applications, in sum, this description should not be construed as limitation of the present invention.

Claims (8)

1. based on an image processing method for laplacian pyramid, it is characterized in that, described method comprises:
The gaussian pyramid that structure input picture is corresponding;
Mediation image is generated according to described gaussian pyramid and mapping function r (x);
Corresponding Laplce Laplace pyramid coefficient is obtained according to described mediation image;
Laplace pyramid coefficient based on described mediation image is outputted on Laplace pyramid accordingly, until described Laplace each point pyramidal is filled, obtains new Laplace pyramid;
According to described new Laplace Pyramid Reconstruction image, and obtain output image;
Wherein, the described step generating mediation image according to described gaussian pyramid and mapping function r (x) comprises: according to described gaussian pyramid and
r ( i ) = g 0 + sign ( i - g 0 ) σ r f d ( i a ) , | i - g 0 | ≤ σ g 0 + sign ( i - g 0 ) [ f e ( | i - g 0 | - σ r ) + σ r ] , otherwise
Generate mediation image;
Wherein, parameter σ rthe threshold values for distinguishing border and texture, g 0the expectation pixel value of this point of surface, function f dand f eby the smooth function of [0,1] Interval Maps to [0,1] interval, f drepresent details enhancing function, f erepresent hue enhancement function, i is the original pixel value of this point, | i-g 0| be the grey scale change in this field, a changes the degree strengthened adjustment details.
2. as claimed in claim 1 based on the image processing method of laplacian pyramid, it is characterized in that, the described step generating mediation image according to described gaussian pyramid and mapping function r (x) comprises:
Detail signal process is carried out to described input picture and the margin signal of described input picture is compressed.
3., as claimed in claim 1 based on the image processing method of laplacian pyramid, it is characterized in that, the step of the gaussian pyramid that described structure input picture is corresponding comprises:
Construct the gaussian pyramid that the image I of size w × h is corresponding, wherein, gaussian pyramid G ithe Gaussian image I reduced by the resolution of I icomposition, i represents the progression of gaussian pyramid, i={0, and 1 ..., j}, image I isize be (w/2 i) × (h/2 i).
4. as claimed in claim 3 based on the image processing method of laplacian pyramid, it is characterized in that, in described gaussian pyramid, every one deck pyramid diagram picture to be reduced by half generation by the wide and height of lower one deck pyramid diagram picture.
5. based on an image processing apparatus for laplacian pyramid, it is characterized in that, described image processing apparatus comprises:
Constructing module, for constructing the corresponding gaussian pyramid of input picture;
Generation module, generates mediation image for the gaussian pyramid that constructs according to described constructing module and mapping function r (x);
Coefficient obtains module, and the mediation image for generating according to described generation module obtains corresponding Laplce Laplace pyramid coefficient;
Laplacian pyramid generation module, for the Laplace pyramid coefficient based on described mediation image is outputted to Laplace pyramid accordingly, until described Laplace each point pyramidal is filled, obtains new Laplace pyramid;
Image Reconstruction module, for the new Laplace Pyramid Reconstruction image generated according to described laplacian pyramid generation module, and obtains output image;
Wherein, described generation module also for according to described gaussian pyramid and
r ( i ) = g 0 + sign ( i - g 0 ) σ r f d ( i a ) , | i - g 0 | ≤ σ g 0 + sign ( i - g 0 ) [ f e ( | i - g 0 | - σ r ) + σ r ] , otherwise
Generate mediation image;
Wherein, parameter σ rthe threshold values for distinguishing border and texture, g 0the expectation pixel value of this point of surface, function f dand f eby the smooth function of [0,1] Interval Maps to [0,1] interval, f drepresent details enhancing function, f erepresent hue enhancement function, i is the original pixel value of this point, | i-g 0| be the grey scale change in this field, a changes the degree strengthened adjustment details.
6., as claimed in claim 5 based on the image processing apparatus of laplacian pyramid, it is characterized in that, described generation module is also for carrying out detail signal process and compressing the margin signal of described input picture to described input picture.
7., as claimed in claim 5 based on the image processing apparatus of laplacian pyramid, it is characterized in that, described constructing module also for the gaussian pyramid that the image I constructing size w × h is corresponding, wherein, gaussian pyramid G ithe Gaussian image I reduced by the resolution of I icomposition, i represents the progression of gaussian pyramid, i={0, and 1 ..., j}, image I isize be (w/2 i) × (h/2 i).
8. as claimed in claim 7 based on the image processing apparatus of laplacian pyramid, it is characterized in that, in described gaussian pyramid, every one deck pyramid diagram picture to be reduced by half generation by the wide and height of lower one deck pyramid diagram picture.
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