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中值滤波器脉冲噪声毕业论文中英文资料外文翻译文献

中值滤波器脉冲噪声毕业论文中英文资料外文翻译文献
中值滤波器脉冲噪声毕业论文中英文资料外文翻译文献

中值滤波器脉冲噪声

中英文资料外文翻译文献Improved 2-D Median Filter for On-Line Impulse Noise Suppressiom

Abstract-An inproved 2-D median filter employing multishell concept to suppress impulse noise ,is presented.The performance of proposed filter is evaluated over image ‘LENA’,The impulsive noise is added using MATLAB utility.The modified strategy reduces the mnuber of replacement and results in better performance and simple hardware realization that is suitable for on-line implementation.

Index terms-Median Filter , Multi-shell Median Filter, Impulse Noise

I.INTRODUCTION

In TV and other imaging systems,impulse noise is a common impairment . The standard T.V.Broadcast signal is often contaminated with impulsive noise arising from various sources such as household electrical appliance and atmospheric disturbances.Broad banding of the signal further increases the level of impulsive noise. V arious filters are proposed to suppress such impairments[1].The median filter(MF)[1-2] is widely used for impulse noise suppression and the multishell median filter(MMF)[3] introduces the concept of missing line recovery. Although these filters

have satisfactory performance, MMF failsto filter two impulse noises in the same prossing window. Moveover,these filters tend to blur the images due to too many replacements. C.J.Juan proposed a modified multishell median filter (MMMF)[4], which removes most of the shortcomings associated with the MF and the MMF. However, it is observed that under certain condions, to be discussed in the follow sections, MMMF fails to perform the desired filtering operation .Moreover,the number of calculations/replacements invoved on the basis of MIN/MAX conditions is still too large and makes the filter difficult to realize,particulariy for real time applications.

In this paper, the threshold strtegy of MMMF is modified so that:

(a)effective noise filtering operations are performed under all

conditions,and

(b)number of calculations/replacements is reduced and simplified. This results in a simple hardware realization of the filter.

II.PROPOSED MODIFICATION

Consider a 3x3-processing window, with P5 as the central pixel,as shown in Figure 1.

P1 P2 P3

P4 P5 P6

P7 P8 P9

Fig.1. A 3x3 processing window

The output of MMMF as proposed in [4] is

Output (X,Y)= Max(P2,P8)if P5﹥Max[S]

P5 if Min [s]﹤Max[S]

Min(P2,P8) if P5﹤Max[S] (1)

Where S is the set of samples surrounding central pixels except(P4.P6)i.e.

S={P1,P2,P3,P7,P8,P9} (2) The principle invoved in the replacement strategy of Equation

(1) is that if P5 is corrupted by noise ,it is better to replace

its gray level by P2 or P8 than by using Min[S] or

Max[S] .also,due to missing lines error,since P4 and P6 may be

lost, they are not considered in Equation(2).

The limitation of Equation(1) is that when Min[S] or Max[S] are

also corrupted by impulse noise,i.e.either Min[S] or Max[S] is

equal to P5,Equation(1)fails to perform the desired filtering operation.To overcome this limitation following modifications

in the replacement strategy of Equation(1),are proposed.

Output (X,Y)= Max(P2,P8)if P5≥Max[S]

P5 if Min [s]<P5<Max[S]

Min(P2,P8) if P5≤Max[S] (3)

It has been observed that more than 70-80% points in an image,the gray level diatances of P5 from(P2 or P8) and from Max[S] are below 16.This is shown in Fig.2 for the image ‘LENA’.This fact is used to further reduce unnessary replacements,thereby reducing the bluring of the images.Thus taking into considertion of Figure(3) can be further modified as

Output (X,Y)= Max(P2,P8)if P5-Max[S]≥16

Max(P2,P8) if Min [s]-P5≥16

P5 otherwise (4)

Equation 4 indicates that replacing action takes place only when the distance between P5 and Min[S] or Max[S] is no smaller than 16. This strtegy thus avoids the necessary replacements and reduces blurring of the images.Moreover,it can be implemented using simple comparators and subtractors.

Gray level distances

Fig.2. Gray level distances between central point and its neighboring points for the image ‘LENNA’

Ⅲ .RESULTS

Figure 3 shows the original image ‘LENNA’and Figure 4 shows the same image when corrupted with impulse noise. Results of median filter and the proposed filter are given in Figures 5 and 6, https://www.doczj.com/doc/774435767.html,paring Figures 5 and 6, it is observed that the result of the proposed filter is much better than those obtained using the median filter. Aithough,the median filter remove the impulsive moise effectively, however,the image gets blurred.The proposed filter removes the impulsive noise and also preserves the details of the image.

A multishell filter employing the modified replacement

strategy is presentde in this paper.The modified filter effectively suppresses the inpulse moise.It uses threshold conditions that require fewer comparisons and replacements and is faster as compared to the other multishell median filters.moreover,it can be realized using simple comparators and subtractors and subtractors and hence can be effectively used in real time applications

改进二维中值滤波器在线脉冲噪声的抑制

摘要:一种改进二维中值滤波器,采用多壳的概念,以抑制脉冲噪声,拟定的过滤器的性能进行评估超过图像“LENNA”的中值滤波,脉冲噪声被添加使用到MATLAB的实用工具中。修改后的策略减少了替换的数量,而且引出适合于上线实施更好的性能以及简单的硬件实现..

关键词:指数计算中值滤波,多壳中值滤波,脉冲噪声

1. 引言

在电视和其他成像系统中,脉冲噪声是一个共同的障碍。标准电视广播信号往往被各种原因产生的脉冲噪声污染,如家电和大气扰动。加宽的信号进一步提高脉冲噪声水平。各种过滤器作出以抑制这种损伤[1],中值滤波器(MF)[1-2]被广泛用于脉冲噪声抑制,多壳中值滤波器(MMF)[3]也介绍了失踪线恢复的概念。尽管这些过滤器有令人满意的表现,MMF的未能在相同的处理窗口,过滤两个脉冲噪声。此外,这些过滤器由于太多的替代趋于模糊的图像。

C.J.Juan提出了改进的多壳中值滤波器(MMMF)[4]。它消除大部分的MF和MMF的缺点。然而,它得在一定条件下才能被使用,此将在后续的章节中讨论。MMMF未能执行所需的过滤操作。此外,在MIN/ MAX的条件基础上的计算/替代量仍然过大,使得过滤器,特别是实时应用,难以实现。

在这个文件中,修改的MMMF限值策略使得:

(一)在任何情况下都进行有效的噪声过滤操作,

(二)减少和简化计算/替换。

这样就有了一个简单的过滤器的硬件实现。

2. 拟议修改

拟定一个3x3的处理窗口,P5作为中央像素,如图1所

P1 P2 P3

P4 P5 P6

P7 P8 P9

图13x3的处理窗口

MMMF由[4]中输出

输出(X,Y)=

这里S是除(P4.P6),围绕中央像素的样本集合

S={P1,P2,P3,P7,P8,P9} (2)

如果P5受噪声污染,在方程(1)替代战略所涉及的原则是,由P2或P8替代其灰度级比使用MIN[S]或Max[S]更好。同时,由于失踪线错误,一旦P4和P6丢失,在方程(2)中他们将不会被考虑。方程(1)的限制,使得本来的Min[S] 或是Max[S]也会被脉冲噪声

损坏,要么是Min[S]要么是Max[S]等于P5,方程(1)未能执行所需过滤操作。为了克服这一限制,接下来再对方程(1)替代策略进行修改。

输出(X,Y)=

在图像中,已观察到70-80%以上的点,从(P2或P8)和Max[S]到P5的距离都低于16。这是图2所示的图像“LENNA”。这实际上是用来进一步减少不必要替代,从而降低图像模糊。因此对图(3)可以进一步修改。

输出(X,Y)=

方程4表示,只有当P5到Min[S] 或者Max[S] 的距离不小于16采取替换措施。这一策略从而避免了必要替换并减少图像模糊。此外,它可以使用简单比较和减法。

灰度水平距离

图2 中央点与其邻近点灰度水平距离(图像LENNA)

图3 图像LENNA检查为100 (灰)点/英寸和8位/像素的扫描

图4 图像LENNA被脉冲莫伊兹损坏

图5 中值滤波器的输出

图6 拟定滤波器的输出

3 结论

图3显示了原始图像LENNA和图4显示了相同图像被脉冲噪声损坏时的图像。在图5和图6分别给出中值滤波结果和拟议的滤波结果。比较图5和6,发现拟议的滤波器结果比使用中值滤波器获取得更好。虽然,中值滤波有效地去除脉冲莫伊兹,但是,图像是模糊的,拟议的滤波器消除脉冲噪声,并保留图像的细节。

本文提出了一个多壳滤波器采用修改后的替换策略,修改后滤波器有效地抑制脉冲噪声,它使用了限值条件,从而运用更少的比较和替换,而且相比其他多壳中值过滤器速度更快。此外,它可以使用简单比较器和减法器来实现,因此可以有效用于实时应用

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