CN103455975A - Method for enhancing edges of synthetic aperture radar images - Google Patents

Abstract

The invention discloses a method for enhancing the edges of synthetic aperture radar images. The method includes computing each pixel in an original synthetic aperture radar image to obtain normalized average ratios of the pixels; using the normalized average ratio of each pixel in the original synthetic aperture radar image as a gray value of the pixel and redrawing a synthetic aperture radar image. The method has the advantages that the average ratios of a sequence are optimized to obtain the gray values of corresponding elements, so that the synthetic aperture radar image can be redrawn, and the strength of the edges of the synthetic aperture radar image is enhanced.

Description

The method that the diameter radar image edge strengthens

Technical field

The present invention relates to the radar image processing technology field, relate in particular to the method that a kind of diameter radar image edge strengthens.

Background technology

Along with the application of synthetic-aperture radar (Synthetic Aperture Radar is called for short SAR) image is more and more extensive, marginal information how to extract diameter radar image becomes the key issue of diameter radar image interpretation decipher.Strengthen visual effect by strengthening the diameter radar image edge, be beneficial to subsequent applications, this has become the important content that diameter radar image is processed.

Diameter radar image is owing to being coherent imaging, make its intrinsic speckle noise greatly affect the marginal information on the image, therefore conventional Edge extraction algorithm is difficult to carry out effective edge extraction, as the spatial domain method of directly original image being processed, comprise Laplce's sharpening, Image multiscale edges enhancing etc., and original image is carried out to certain conversion, as wavelet transformation etc., at transform domain, processed to realize the figure image intensifying.As Laplce's sharpening of image is to utilize Laplace operator image to be carried out to a kind of method of edge enhancing, it is basis that Laplace operator be take pixel grey scale Difference Calculation in Image neighborhood, and a kind of Image neighborhood of deriving by second-order differential strengthens algorithm.Its basic thought is, when the center pixel gray scale of neighborhood lower than its place neighborhood in during the average gray of other pixels, the gray scale of this center pixel should be further reduced, when the center pixel gray scale of neighborhood higher than its place neighborhood in during the average gray of other pixels, the gray scale of this center pixel should be further improved, and the sharpening that realizes image with this is processed.In the algorithm implementation procedure, Laplce's sharpening algorithm by the four directions to centre of neighbourhood pixel to or from all directions to asking gradient, and by the relation of other pixel grey scales in gradient and phase Calais judgement center pixel gray scale and neighborhood, and by the result of gradient computing, pixel grey scale is adjusted.

Visible, said method of the prior art is all the amplitude that promotes original high fdrequency component in image, do not produce new radio-frequency component, and the speckle noise of diameter radar image is typical case's property taken advantage of characteristic, these edge enhancing method effects are very limited, can't obtain satisfied edge and strengthen result.

Summary of the invention

(1) technical matters that will solve

For solving above-mentioned one or more problems, the invention provides the method that a kind of diameter radar image edge strengthens, the effect strengthened to improve edge.

(2) technical scheme

According to an aspect of the present invention, the method that provides a kind of diameter radar image edge to strengthen, comprising: for each pixel in the synthetic-aperture radar original image, calculate its normalization average value ratio; Be compared to the gray-scale value of this pixel with the normalization average value of each pixel in the synthetic-aperture radar original image, repaint diameter radar image.

(3) beneficial effect

From technique scheme, can find out, diameter radar image edge enhancing method of the present invention has following beneficial effect: the present invention utilizes the otherness between the big or small ROA calculated of different windows to strengthen the marginal information of diameter radar image, further sharpening the edge strength of diameter radar image, improve the effect that edge strengthens, be conducive to rim detection and the extraction of diameter radar image.

The accompanying drawing explanation

The process flow diagram that Fig. 1 is embodiment of the present invention diameter radar image edge enhancing method;

Fig. 2 calculates the average of diameter radar image than building the schematic diagram of window in step in embodiment of the present invention diameter radar image edge enhancing method; Wherein, the schematic diagram that Fig. 2 A is horizontal direction, the schematic diagram that Fig. 2 B is vertical direction; The schematic diagram that Fig. 2 C is left-leaning direction; The schematic diagram that Fig. 2 D is the Right deviation direction.

Fig. 3 is the original diameter radar image of inputting in embodiment of the present invention diameter radar image edge enhancing method;

Fig. 4 calculates the average ratio that window size is 3 in embodiment of the present invention diameter radar image edge enhancing method;

Fig. 5 calculates the average ratio that window size is 5 in embodiment of the present invention diameter radar image edge enhancing method;

Fig. 6 calculates the average ratio that window size is 7 in embodiment of the present invention diameter radar image edge enhancing method;

Fig. 7 is for using the present invention to execute the diameter radar image after routine diameter radar image edge enhancing method is processed the original diameter radar image of Fig. 3.

Embodiment

For making the purpose, technical solutions and advantages of the present invention clearer, below in conjunction with specific embodiment, and, with reference to accompanying drawing, the present invention is described in more detail.

It should be noted that, in accompanying drawing or instructions description, similar or identical part is all used identical figure number.With simplification or convenience, indicate in the accompanying drawings, and the implementation that does not illustrate in accompanying drawing or describe, be form known to a person of ordinary skill in the art in affiliated technical field.In addition, although this paper can provide the demonstration of the parameter that comprises particular value, should be appreciated that, parameter is without definitely equaling corresponding value, but can in acceptable error margin or design constraint, be similar to corresponding value.

The method that diameter radar image of the present invention edge strengthens, utilize different windows size to calculate the average of correspondence of diameter radar image than (Ratio Of Averages, be called for short ROA), then the ROA of these different windows is combined, calculate the best normalization differential index (di) on same picture position, extract best normalization differential index (di) and carry out sharpening, thereby realize that the edge of diameter radar image strengthens.

In one exemplary embodiment of the present invention, a kind of process flow diagram of diameter radar image edge enhancing method has been proposed.The process flow diagram that Fig. 1 is embodiment of the present invention diameter radar image edge enhancing method.As shown in Figure 1, the present embodiment comprises the following steps:

Step S102, for each pixel in the synthetic-aperture radar original image, calculate its normalization average value ratio;

Wherein, for a pixel in the synthetic-aperture radar original image, calculate its normalized step and further comprise:

Step S102a, utilize the square window of N different sizes to calculate the average ratio of this pixel, obtains average based on the big or small square window of difference than sequence, and wherein N is for being greater than 2 integers;

Wherein, for a pixel in the synthetic-aperture radar original image, the square window size of take compares R as w1 calculates its average _w1:

$R_{w1}=\min \left(R_{w1}^k\right)---\left(1\right)$

$\begin{array}{cc}{R}_{w1}^k=\min (P_{w1}^k/Q_{w1}^k,Q_{w1}^k/P_{w1}^k)& k=\mathrm{1,2,3,4}---\left(2\right)\end{array}$

In formula (1) and (2),

be illustrated in minute average ratio that two side areas dividing mode in k is calculated, min () means to get of minimum wherein,

be respectively the average gray value of this pixel two side areas pixel, k means the dividing mode of two side areas.

Fig. 2 be in the embodiment of the present invention diameter radar image edge enhancing method computation of mean values than the schematic diagram that builds window in step.As shown in Figure 2, centered by this pixel, two adjacent and zero lap is regional for the square window of w1 * w1 pixel is divided into by it for size.Wherein:

During k=1, $\begin{array}{c}{R}_{w1}^1=\min (P_{w1}^1/Q_{w1}^1,Q_{w1}^1/P_{w1}^1),\end{array}$

respectively upper-side area pixel average gray value and the underside area pixel average gray value of this pixel, as shown in Figure 2 A;

During k=2, $\begin{array}{c}{R}_{w1}^2=\min (P_{w1}^2/Q_{w1}^2,Q_{w1}^2/P_{w1}^2),\end{array}$

respectively left field pixel average gray value and the right side area pixel average gray value of this pixel, as shown in Fig. 2 B;

During k=3, $R_{w1}^3=\min (P_{w1}^3/Q_{w1}^3,Q_{w1}^3/P_{w1}^3),$

respectively upper right side area pixel average gray value and the left underside area pixel average gray value of this pixel, as shown in Figure 2 C;

During k=4, $\begin{array}{c}{R}_{w1}^k=\min (P_{w1}^4/Q_{w1}^4,Q_{w1}^4/P_{w1}^4),\end{array}$

respectively upper left side area pixel average gray value and the lower right side area pixel average gray value of this pixel, as shown in Figure 2 D.

Except the two side areas dividing mode that Fig. 2 provides, those skilled in the art it will also be appreciated that other regional dividing mode, will not enumerate herein.And regional dividing mode herein also can be three kinds, five kinds etc., also no longer describe in detail herein.

Fig. 3 is the original diameter radar image of input.Fig. 4-Fig. 6 is for using the different windows size ROA value after the embodiment of the present invention is processed the original diameter radar image of Fig. 3, and Fig. 4 is the ROA that the calculation window size is 3; Fig. 5 is the ROA that the calculation window size is 5; Fig. 6 is the ROA that the calculation window size is 7.

In this step, get w1 for different sizes and be greater than 1 odd number numerical value, and obtaining the window of different sizes, just can calculate a series of ROA value to each pixel.In this step, w1 at least needs to get two values, but preferably should get 3 values, and the span of w1 is 3,5,7,9,11,13,15 etc., preferably, N=3, the w1 value is 3,5,7.The average obtained can be expressed as than sequence: [R ₃, R ₅, R ₇].

Step S102b, choose the maximal value R of average ratio in than sequence in described average _maxwith minimum value R _min;

Step S102c, utilize the maximal value R of this average ratio _maxwith minimum value R _min, calculate the best normalization differential index (di) of this pixel:

$I(x,y)=\frac{R_{\max }-R_{\min }}{R_{\max }+R_{\min }}---\left(3\right)$

Wherein, the lateral attitude of pixel in the x presentation video, the lengthwise position of pixel in the y presentation video.

Step S102d: according to described best normalization differential index (di), calculate normalization average value ratio that should pixel:

E(x，y)＝[1.0-I(x，y)]×255.0 (4)

Step S104, be compared to the gray-scale value of this pixel with the normalization average value of each pixel in the synthetic-aperture radar original image, repaint diameter radar image.

Fig. 7 is for using the diameter radar image after embodiment of the present invention diameter radar image edge enhancing method is processed the original diameter radar image of Fig. 3.As shown in Figure 7, the diameter radar image after processing, the acutance at its edge has been got back and has been improved greatly than Fig. 4-Fig. 6.

Method of the present invention contributes to promote diameter radar image rim detection and extraction, can be widely used in the fields such as diameter radar image coupling, the extraction of atural object profile and identification.

Above-described specific embodiment; purpose of the present invention, technical scheme and beneficial effect are further described; institute is understood that; the foregoing is only specific embodiments of the invention; be not limited to the present invention; within the spirit and principles in the present invention all, any modification of making, be equal to replacement, improvement etc., within all should being included in protection scope of the present invention.

Claims (7)

1. the method that a diameter radar image edge strengthens comprises:

For each pixel in the synthetic-aperture radar original image, calculate its normalization average value ratio:

Be compared to the gray-scale value of this pixel with the normalization average value of each pixel in the synthetic-aperture radar original image, repaint diameter radar image.

2. the method that diameter radar image according to claim 1 edge strengthens, adopt following methods, calculates the normalization average value ratio of a pixel in the synthetic-aperture radar original image:

Utilize N the different edge little square window of growing up to calculate the average ratio of this pixel, obtain comparing sequence based on the grow up average of little square window of different edge;

Choose maximal value and the minimum value of average ratio in than sequence in described average;

Utilize maximal value and the minimum value of described average ratio, calculate the best normalization differential index (di) of this pixel;

According to described best normalization differential index (di), calculate the normalization average value ratio of this pixel.

3. the method that diameter radar image according to claim 2 edge strengthens, be the square window of w1 pixel for length of side size, and according to following formula, the average of calculating this pixel compares R _w1:

$R_{w1}=\min \left(R_{w1}^k\right)$

$\begin{array}{c}{R}_{w1}^k=\min (P_{w1}^k/Q_{w1}^k,Q_{w1}^k/P_{w1}^k)\end{array}$

Wherein, min () means to get wherein minimum one,

respectively this pixel two side areas pixel average gray value under k kind two side areas dividing mode,

be illustrated in minute average ratio that k kind two side areas dividing mode is calculated, k means the dividing mode of this pixel two side areas.

4. the method that diameter radar image according to claim 3 edge strengthens, described k=1,2,3,4;

$\begin{array}{c}{R}_{w1}=\min (R_{w1}^1/R_{w1}^2,R_{w1}^3/R_{w1}^4)\end{array}$

Wherein:

During k=1, $\begin{array}{c}{R}_{w1}^1=\min (P_{w1}^1/Q_{w1}^1,Q_{w1}^1/P_{w1}^1),\end{array}$

respectively upper-side area pixel average gray value and the underside area pixel average gray value of this pixel;

During k=2, $\begin{array}{c}{R}_{w1}^2=\min (P_{w1}^2/Q_{w1}^2,Q_{w1}^2/P_{w1}^2),\end{array}$ respectively left field pixel average gray value and the right side area pixel average gray value of this pixel;

During k=3, $\begin{array}{c}{R}_{w1}^3=\min (P_{w1}^3/Q_{w1}^3,Q_{w1}^3/P_{w1}^3),\end{array}$

respectively upper right side area pixel average gray value and the left underside area pixel average gray value of this pixel;

During k=4, $\begin{array}{c}{R}_{w1}^k=\min (P_{w1}^4/Q_{w1}^4,Q_{w1}^4/P_{w1}^4),\end{array}$

respectively upper left side area pixel average gray value and the lower right side area pixel average gray value of this pixel.

5. the method that diameter radar image according to claim 3 edge strengthens, wherein, described N=3, described w1=3,5,7.

6. the method strengthened according to the described diameter radar image of any one in claim 2 to 5 edge, adopt following formula, calculates the best normalization differential index (di) of this pixel:

$I(x,y)=\frac{R_{\max }-R_{\min }}{R_{\max }+R_{\min }}$

Wherein, R _maxfor the maximal value of average ratio, R _minminimum value for the average ratio.

7. the method that diameter radar image according to claim 6 edge strengthens, adopt following formula, calculates the normalization average value ratio of this pixel:

E(x，y)＝[1.0-I(x，y)]×255.0。

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