CN102800086A - Offshore scene significance detection method - Google Patents

Offshore scene significance detection method Download PDF

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CN102800086A
CN102800086A CN2012102072715A CN201210207271A CN102800086A CN 102800086 A CN102800086 A CN 102800086A CN 2012102072715 A CN2012102072715 A CN 2012102072715A CN 201210207271 A CN201210207271 A CN 201210207271A CN 102800086 A CN102800086 A CN 102800086A
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significantly
brightness
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marine scene
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CN102800086B (en
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任蕾
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Shanghai Maritime University
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Shanghai Maritime University
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Abstract

The invention discloses an offshore scene significance detection method. The method comprises the following steps of: 1, extracting an offshore scene image sequence; 2, transferring each frame image to the CIELab colour space, and extracting the characteristic pattern of luminance and colour passages; 3, using the absolute value of the difference between the extracted characteristics and the global mid value as the global significance map; 4, using the absolute value of the difference between the characteristics and the local mean value filtration as the local significance map; 5, combining the global significance map and the local significance map of the characteristics to obtain an overall significance map; 6, linearly combining the significance maps of the colour passages of frame images, and respectively combining the combined significance maps with the luminance significance maps to form an overall significance map; 7, accumulating by using each frame detection result as the centre and modifying the significance map of the current frame; and 8, converting the overall significance map into a binarization image to obtain an offshore scene significance target area. By adopting the method, the significance area in the offshore scene can be extracted rapidly, and the interference of sea noise wave can be favorably inhibited. The method is simple in implementation, and is suitable for real-time application.

Description

A kind of marine scene conspicuousness detection method
Technical field
The present invention relates to the detection technique of a kind of machine vision and image processing field, be specifically related to the marine scene conspicuousness detection method that a kind of utilization utilizes Flame Image Process and machine vision technique.
Background technology
At present, domestic and international most visual attention computation model directly carries out conspicuousness in the spatial domain of image and detects, and extracts significantly figure.These class methods are utilized the thinking of image spectrum relatively, need not image carried out orthogonal transformations such as Fourier transform or discrete cosine transform.
Based on the conspicuousness detection method of spatial domain, its core is how to define conspicuousness.Each class methods that proposes are at present mainly utilized the feature difference tolerance conspicuousness between the spatial domain pixel, and common feature comprises brightness, color, direction, texture etc.Simultaneously, a lot of scholars introduce information theory, graph theory and bayesian theory etc. in the calculating of conspicuousness, in the natural scene conspicuousness detects, have obtained better effects.Significantly scheme the not high problem of resolution in order to solve frequency domain conspicuousness detection method; Frequency tuning conspicuousness detection method (the Frequency tuned method that propositions such as Achanta realize on former figure size; FrT), each characteristic mean in the definition image C IELab color space be significance to the difference value behind its gaussian filtering.This method is simple and easy to realize that can extract more complete well-marked target, its internal consistency is good.
The scholar of domestic part to based on ship detection problem in the marine scene of visible images, uses vision noticing mechanism and has carried out preliminary discussion.Leaf is intelligent to wait the people to propose the (Hue based on HIS; Saturation, Intensity) boats and ships in space detect visual attention model, promptly in the HSI color space; Adopt multiple dimensioned Difference Calculation to obtain each component characteristic pattern to three components, and then it is carried out significantly figure of linearity fusion acquisition.Introduce vision noticing mechanism in people such as Wu Qiying moving target monitoring in real time at sea and the tracker, proposed a kind of linear LPF method based on the little template of inverted triangle of iteration, the smoothing denoising on the Rapid Realization coarse resolution image highlights target with this.Wu Qiying etc. also propose the movement overseas target method for quick based on the visible images sequence; Utilize at first segmented sense region-of-interest (ROI in still image of visual attention model; Region of interest), and then only the time differencing method of application enhancements detects moving target in area-of-interest.
Yet there is limitation in the method for these propositions.At first, notice that these methods all are that therefore, mostly target is general objective to the detection of well-marked target in natural scene or the land scene; Simultaneously, because algorithm is complicated, before carrying out conspicuousness calculating, often need carry out down-sampling to original image.As far as large-sized well-marked target, down-sampling can not cause target information to be lost too much, so the conspicuousness testing result is more satisfactory.But because the singularity of marine scene, promptly mostly naval target is little target, especially point target; And be scattered in the marine scene; Therefore directly use existing spatial domain conspicuousness detection method, its result is undesirable, and is especially not good enough to the detection effect of little target; Analyzing its essential reason, is because image down sampling causes little target information to be lost too much.Frequency tuning conspicuousness detection method realizes simple; But owing to only considered that global contrast as conspicuousness, directly applies to marine scene with it in this model, because the characteristic of a large amount of extra large clutters; All be higher than characteristic mean far away; Be that its global contrast and target are very approaching, cause the testing result target, also comprised a large amount of clutters by outside outstanding.In addition, existing marine scene visual attention model has been used for reference the visual attention computation model of Itti, realizes relative complex.
In sum, existing related work mainly solves the conspicuousness detection problem in land scene or the natural scene.Because exist a large amount of extra large clutters and naval target to be mostly little target in the marine scene, the existing methods effect is undesirable.To the defective of prior art, a kind of new marine scene conspicuousness detection method of utilizing is proposed especially, with the problem of mentioning more than solving.
Summary of the invention
The invention provides a kind of marine scene conspicuousness detection method, utilize the characteristic of marine scene image self, realize extracting marking area at the CIELab color space.
For realizing above-mentioned purpose, the invention provides a kind of marine scene conspicuousness detection method, be characterized in that the method includes the steps of:
Step 1, the marine scene image sequence of extraction;
Every two field picture of step 2, marine scene image to the CIELab color space, and extracts its brightness and two Color Channels as essential characteristic by the RGB color space conversion, obtains the characteristic pattern of brightness and two Color Channels;
The brightness of all two field pictures of step 3, marine scene image and two color characteristics absolute value of median difference overall with it are respectively significantly schemed as the overall situation;
If of input image sequence
Figure 2012102072715100002DEST_PATH_IMAGE002
Frame
Figure 2012102072715100002DEST_PATH_IMAGE004
, L iBe brightness, a iAnd b iBe two color characteristics, this is years old
Figure 2012102072715100002DEST_PATH_IMAGE002A
Frame is any frame in the marine scene image;
To brightness and two color characteristics, calculate its overall intermediate value respectively,
Figure 2012102072715100002DEST_PATH_IMAGE006
（1）
Figure 2012102072715100002DEST_PATH_IMAGE008
（2）
Figure 2012102072715100002DEST_PATH_IMAGE010
（3）
L wherein ImBe the overall intermediate value of brightness, a ImAnd b ImIt is the overall intermediate value of two colors;
Then, the overall situation of calculating each characteristic is significantly schemed:
Figure 2012102072715100002DEST_PATH_IMAGE012
（4）
Figure 2012102072715100002DEST_PATH_IMAGE014
（5）
Figure 2012102072715100002DEST_PATH_IMAGE016
（6）
Wherein, Represent absolute value;
Figure 2012102072715100002DEST_PATH_IMAGE017
is that the overall situation of brightness is significantly schemed, and
Figure 2012102072715100002DEST_PATH_IMAGE018
and
Figure 2012102072715100002DEST_PATH_IMAGE019
is respectively the remarkable figure of the overall situation of two color characteristics;
The brightness of all two field pictures of step 4, marine scene image and two color characteristics are significantly schemed as the part with the absolute value of its local mean value filtering difference respectively:
Figure 2012102072715100002DEST_PATH_IMAGE021
（7）
Figure 2012102072715100002DEST_PATH_IMAGE023
（8）
Figure 2012102072715100002DEST_PATH_IMAGE025
（9）
Wherein,
Figure 2012102072715100002DEST_PATH_IMAGE027
is the local mean value template of
Figure 2012102072715100002DEST_PATH_IMAGE029
; I.e.
Figure 2012102072715100002DEST_PATH_IMAGE031
; Symbol
Figure 2012102072715100002DEST_PATH_IMAGE033
representation space territory convolution algorithm;
Figure 2012102072715100002DEST_PATH_IMAGE034
is the local significantly figure of brightness, and
Figure 2012102072715100002DEST_PATH_IMAGE035
and
Figure 2012102072715100002DEST_PATH_IMAGE036
is the local significantly figure of two color characteristics;
The overall situation of the brightness of all two field pictures of step 5, marine scene image and two color characteristics is significantly schemed and local significantly figure merges respectively, obtains the total of these three characteristics and significantly schemes:
Figure 2012102072715100002DEST_PATH_IMAGE038
（10）
Figure 2012102072715100002DEST_PATH_IMAGE040
（11）
Figure 2012102072715100002DEST_PATH_IMAGE042
（12）
Wherein,
Figure 2012102072715100002DEST_PATH_IMAGE043
is total significantly figure of brightness, and
Figure 2012102072715100002DEST_PATH_IMAGE044
and
Figure 2012102072715100002DEST_PATH_IMAGE045
is total significantly figure of two color characteristics;
The remarkable figure of two Color Channels of all two field pictures of step 6, marine scene image carries out linearity respectively and merges, and significantly schemes to be fused to total significantly figure with its brightness respectively again;
In every frame, the linear remarkable figure of the Color Channel that obtains that merges of the remarkable figure of two Color Channels is:
Figure 2012102072715100002DEST_PATH_IMAGE047
（13）
Wherein,
Figure 2012102072715100002DEST_PATH_IMAGE048
significantly schemes for Color Channel;
Color Channel is significantly schemed significantly to scheme to merge with brightness, obtains the total remarkable figure of the marine scene of this frame:
（14）
Wherein,
Figure 2012102072715100002DEST_PATH_IMAGE051
is total significantly figure of the marine scene of
Figure 2012102072715100002DEST_PATH_IMAGE002AA
frame
Figure 2012102072715100002DEST_PATH_IMAGE004A
of input image sequence;
Step 7, to every frame testing result, utilizing with it is the center, with the time window of regular length, should be in the time altogether the corresponding significantly figure of n frame accumulate, the remarkable figure of present frame is revised:
Figure 2012102072715100002DEST_PATH_IMAGE053
（15）
Wherein
Figure 2012102072715100002DEST_PATH_IMAGE055
is the length of time window;
Figure 2012102072715100002DEST_PATH_IMAGE057
is the normalization sign of operation;
Step 8, according to preset threshold, convert total significantly figure into binary image, obtain marine scene well-marked target zone.
In the above-mentioned step 7, n desirable 5 or 7 or 9 or 11.
Threshold value described in the above-mentioned step 8 is a normalized threshold, and its span is 0.2 to 0.5.
A kind of marine scene conspicuousness detection method of the present invention is compared with prior art; Its advantage is; Marking area in can the rapid extraction marine scene of use of the present invention helps target detection in the marine scene, better inhibited the interference of extra large clutter; Under situation about flooded by wave the medium and small target of some frame and the situation that stronger extra large noise jamming occurs, guarantee the detection of marine remarkable little target.Method of the present invention realizes simple, is fit to use in real time, and the supplementary means of machine vision can be provided for all kinds of maritime affairs monitor staff.
Description of drawings
Fig. 1 is the method flow diagram of a kind of marine scene conspicuousness detection method of the present invention.
Embodiment
Below in conjunction with accompanying drawing, further specify specific embodiment of the present invention.
The invention discloses a kind of marine scene conspicuousness detection method, utilize the space domain characteristic of marine scene image, in the conspicuousness detection method of CIELab color space realization.This method is utilized the overall situation and the local conspicuousness of marine scene, extracts significantly figure and it is merged of brightness of image and Color Channel respectively, with outstanding target area.Simultaneously,, further remove extra large clutter, the remarkable figure between multiframe is accumulated in order to strengthen the marking area of marine scene.
The present invention is a space domain characteristic of utilizing marine scene image, in the conspicuousness detection method of CIELab color space realization.Utilize marine scene image brightness and the Color Channel overall situation and the local significantly fusion of figure in this method, obtain marking area.Simultaneously, in order better to remove extra large clutter, adopted simple interframe conspicuousness accumulation method.
The present invention has mainly adopted when implementing: the conspicuousness computing method of the marine scene image of every frame, and interframe is significantly schemed accumulation method.
The present invention can be applicable to search and rescue in the perils of the sea, the maritime affairs patrol, based on fields such as the ship collision prevention of video, anti-pirate monitoring, Zhi Ban lookouts, the while with infrared, remote sensing, radar imagery is technological combines, can be maritime traffic safety etc. comprehensive visual information be provided.
As shown in Figure 1, the marine scene conspicuousness of the present invention detection method comprises following steps:
Step 1, utilize video capture device (for example video camera etc.), obtain original marine image sequence, extract marine scene image sequence.
Every two field picture of step 2, marine scene image to the CIELab color space, and extracts its luminance channel L and two Color Channel a and b as essential characteristic by the RGB color space conversion, obtains the characteristic pattern of brightness and two Color Channels.
This is owing to correlativity between each passage in the RGB color space is higher, therefore adopts the CIELab color space, extracts the brightness and the color characteristic of visual scene.
Wherein above-mentioned CIELab color space has only two color space a or b.
The brightness of all two field pictures of step 3, marine scene image and two color characteristics absolute value of median difference overall with it are respectively significantly schemed as the overall situation.
Calculation process is an example with a frame wherein, establishes of input image sequence
Figure DEST_PATH_IMAGE002AAA
Frame
Figure DEST_PATH_IMAGE004AA
, its brightness and two color characteristics are respectively:
Figure DEST_PATH_IMAGE059
, L iBe brightness, a iAnd b iBe two color characteristics.
To brightness and two color characteristics, calculate its overall intermediate value respectively,
Figure DEST_PATH_IMAGE006A
（1）
Figure DEST_PATH_IMAGE008A
（2）
Figure DEST_PATH_IMAGE010A
（3）
L wherein ImBe the overall intermediate value of brightness, a ImAnd b ImIt is the overall intermediate value of two colors.
And utilize the overall situation of each characteristic of computes significantly to scheme, be respectively:
Figure DEST_PATH_IMAGE012A
（4）
Figure DEST_PATH_IMAGE014A
（5）
Figure DEST_PATH_IMAGE016A
（6）
Wherein, Represent absolute value;
Figure DEST_PATH_IMAGE017A
is that the overall situation of brightness is significantly schemed, and
Figure DEST_PATH_IMAGE018A
and is respectively the remarkable figure of the overall situation of two color characteristics.
The brightness of all two field pictures of step 4, marine scene image and two color characteristics are significantly schemed as the part with the absolute value of its local mean value filtering difference respectively.
With frame is example; The absolute value that utilizes each characteristic local mean value filtering and each characteristic difference is respectively above-mentioned three passages as its local significantly figure:
Figure DEST_PATH_IMAGE021A
（7）
Figure DEST_PATH_IMAGE023A
（8）
（9）
Wherein,
Figure DEST_PATH_IMAGE027A
is the local mean value template of
Figure DEST_PATH_IMAGE029A
, i.e.
Figure DEST_PATH_IMAGE031A
.Symbol
Figure DEST_PATH_IMAGE033A
representation space territory convolution algorithm.
Figure DEST_PATH_IMAGE034A
is the local significantly figure of brightness, and and
Figure DEST_PATH_IMAGE036A
is the local significantly figure of two color characteristics.
The overall situation of the brightness of all two field pictures of step 5, marine scene image and two color characteristics is significantly schemed and local significantly figure merges respectively, obtains the total of these three characteristics and significantly schemes.
With
Figure DEST_PATH_IMAGE002AAAAA
frame is example, and total significantly figure of brightness and two color characteristics is shown below:
Figure DEST_PATH_IMAGE038A
（10）
（11）
Figure DEST_PATH_IMAGE042A
（12）
Wherein,
Figure DEST_PATH_IMAGE043A
is total significantly figure of brightness, and
Figure DEST_PATH_IMAGE044A
and
Figure DEST_PATH_IMAGE045A
is total significantly figure of two color characteristics.
The remarkable figure of two Color Channels of all two field pictures of step 6, marine scene image carries out linearity respectively and merges, and significantly schemes to be fused to total significantly figure with its brightness respectively again.
With
Figure DEST_PATH_IMAGE002AAAAAA
frame is example, and the linear remarkable figure of the Color Channel that obtains that merges of the remarkable figure of two Color Channels is:
Figure DEST_PATH_IMAGE047A
（13）
Wherein,
Figure DEST_PATH_IMAGE048A
significantly schemes for Color Channel.
The result and the brightness of following formula (13) are significantly schemed to merge, and the total significantly figure that finally obtains the marine scene of this frame is:
（14）
Wherein,
Figure DEST_PATH_IMAGE051A
is total significantly figure of the marine scene of
Figure DEST_PATH_IMAGE002AAAAAAA
frame
Figure DEST_PATH_IMAGE004AAA
of input image sequence.
 
Step 7, to every frame testing result, utilizing with it is the center, the testing result of each 3 frame of front and back is significantly schemed accumulation; To preceding 3 frames and back 3 two field pictures of image sequence, then utilize continuous 7 frames that comprise this frame significantly to scheme to accumulate.
The present invention utilizes the time window of regular length, and corresponding significantly figure accumulates with all frames in this time, and the remarkable figure of present frame is revised, and purpose is to strengthen target, suppresses extra large clutter.
Be that the remarkable figure of revised
Figure DEST_PATH_IMAGE060
frame is:
Figure DEST_PATH_IMAGE053A
（15）
Wherein
Figure DEST_PATH_IMAGE055A
is the length of time window; The value of n is generally got odd number; N desirable 5 or 7 or 9 or 11 for example; The value of this n can not be excessive or too small, and the frame per second when itself and video acquisition has relation.
Figure DEST_PATH_IMAGE055AA
gets 7 in the present embodiment;
Figure DEST_PATH_IMAGE057A
; It is the normalization sign of operation; Purpose is the gray-scale value of significantly scheming is united, so that the accumulation of the conspicuousness of back.
Special, to preceding 3 frames and last 3 frames of image sequence, then significantly scheme to do accumulation with continuous 7 frames that comprise this frame.
Step 8, according to preset threshold, convert total significantly figure into binary image, obtain marine scene well-marked target zone.Wherein above-mentioned preset threshold value is a normalized threshold, and its span is the numerical value between 0.2 to 0.5, and this threshold value is an empirical value.
Although content of the present invention has been done detailed introduction through above-mentioned preferred embodiment, will be appreciated that above-mentioned description should not be considered to limitation of the present invention.After those skilled in the art have read foregoing, for multiple modification of the present invention with to substitute all will be conspicuous.Therefore, protection scope of the present invention should be limited appended claim.

Claims (3)

1. marine scene conspicuousness detection method is characterized in that the method includes the steps of:
Step 1, the marine scene image sequence of extraction;
Every two field picture of step 2, marine scene image to the CIELab color space, and extracts its brightness and two Color Channels as essential characteristic by the RGB color space conversion, obtains the characteristic pattern of brightness and two Color Channels;
The brightness of all two field pictures of step 3, marine scene image and two color characteristics absolute value of median difference overall with it are respectively significantly schemed as the overall situation;
If of input image sequence Frame
Figure 2012102072715100001DEST_PATH_IMAGE004
, L iBe brightness, a iAnd b iBe two color characteristics, this is years old
Figure DEST_PATH_IMAGE002A
Frame is any frame in the marine scene image;
To brightness and two color characteristics, calculate its overall intermediate value respectively,
Figure 2012102072715100001DEST_PATH_IMAGE006
（1）
Figure 2012102072715100001DEST_PATH_IMAGE008
（2）
Figure 2012102072715100001DEST_PATH_IMAGE010
（3）
L wherein ImBe the overall intermediate value of brightness, a ImAnd b ImIt is the overall intermediate value of two colors;
Then, the overall situation of calculating each characteristic is significantly schemed:
Figure 2012102072715100001DEST_PATH_IMAGE012
（4）
（5）
Figure 2012102072715100001DEST_PATH_IMAGE016
（6）
Wherein, Represent absolute value;
Figure 2012102072715100001DEST_PATH_IMAGE017
is that the overall situation of brightness is significantly schemed, and and
Figure 2012102072715100001DEST_PATH_IMAGE019
is respectively the remarkable figure of the overall situation of two color characteristics;
The brightness of all two field pictures of step 4, marine scene image and two color characteristics are significantly schemed as the part with the absolute value of its local mean value filtering difference respectively:
Figure DEST_PATH_IMAGE021
（7）
Figure DEST_PATH_IMAGE023
（8）
（9）
Wherein,
Figure DEST_PATH_IMAGE027
is the local mean value template of ; I.e.
Figure DEST_PATH_IMAGE031
; Symbol representation space territory convolution algorithm;
Figure DEST_PATH_IMAGE034
is the local significantly figure of brightness, and
Figure DEST_PATH_IMAGE035
and
Figure DEST_PATH_IMAGE036
is the local significantly figure of two color characteristics;
The overall situation of the brightness of all two field pictures of step 5, marine scene image and two color characteristics is significantly schemed and local significantly figure merges respectively, obtains the total of these three characteristics and significantly schemes:
Figure DEST_PATH_IMAGE038
（10）
Figure DEST_PATH_IMAGE040
（11）
Figure DEST_PATH_IMAGE042
（12）
Wherein,
Figure DEST_PATH_IMAGE043
is total significantly figure of brightness, and
Figure DEST_PATH_IMAGE044
and
Figure DEST_PATH_IMAGE045
is total significantly figure of two color characteristics;
The remarkable figure of two Color Channels of all two field pictures of step 6, marine scene image carries out linearity respectively and merges, and significantly schemes to be fused to total significantly figure with its brightness respectively again;
In every frame, the linear remarkable figure of the Color Channel that obtains that merges of the remarkable figure of two Color Channels is:
Figure DEST_PATH_IMAGE047
（13）
Wherein,
Figure DEST_PATH_IMAGE048
significantly schemes for Color Channel;
Color Channel is significantly schemed significantly to scheme to merge with brightness, obtains the total remarkable figure of the marine scene of this frame:
Figure DEST_PATH_IMAGE050
（14）
Wherein, is total significantly figure of the marine scene of
Figure DEST_PATH_IMAGE002AA
frame
Figure DEST_PATH_IMAGE004A
of input image sequence;
Step 7, to every frame testing result, utilizing with it is the center, with the time window of regular length, should be in the time altogether the corresponding significantly figure of n frame accumulate, the remarkable figure of present frame is revised:
Figure DEST_PATH_IMAGE053
（15）
Wherein
Figure DEST_PATH_IMAGE055
is the length of time window;
Figure DEST_PATH_IMAGE057
is the normalization sign of operation;
Step 8, according to preset threshold, convert total significantly figure into binary image, obtain marine scene well-marked target zone.
2. a kind of marine scene conspicuousness detection method as claimed in claim 1 is characterized in that, in the described step 7, and n desirable 5 or 7 or 9 or 11.
3. a kind of marine scene conspicuousness detection method as claimed in claim 1 is characterized in that the threshold value described in the described step 8 is a normalized threshold, and its span is 0.2 to 0.5.
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