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On zerotree quantization for embedded wavelet packet image coding

On zerotree quantization for embedded wavelet packet image coding
On zerotree quantization for embedded wavelet packet image coding

On Zerotree Quantization for Embedded Wavelet Packet Image

Coding

N.M.Rajpoot1,2,F.G.Meyer3,R.G.Wilson1,and R.R.Coifman2

1Department of Computer Science,University of Warwick,Coventry,United Kingdom Department of2Mathematics and3Computer Science,Yale University,New Haven,CT

e-mail:rajpoot-nasir@https://www.doczj.com/doc/109175558.html,

Abstract

Wavelet packets are an e?ective representation tool for adaptive waveform analysis of a given signal.We ?rst combine the wavelet packet representation with zerotree quantization for image coding.A general ze-rotree structure is de?ned which can adapt itself to any arbitrary wavelet packet basis.We then describe an e?cient coding algorithm based on this structure.Fi-nally,the hypothesis for prediction of coe?cients from coarser scale to?ner scale is tested and its e?ective-ness is compared with that of zerotree hypothesis for wavelet coe?cients.

1Introduction

There has been a surge of interest in wavelet trans-forms for image and video coding applications,in re-cent years.This is mainly due to the nice localiza-tion properties of wavelets in both time(or space) and frequency.The zerotree quantization,proposed by Shapiro[8],is an e?ective way of exploiting the self-similarities among high-frequency subbands at vari-ous resolutions.The main thrust of this quantization strategy is in the prediction of corresponding wavelet coe?cients in higher frequency subbands at the?ner scales,by exploiting the parent-o?spring dependen-cies.This prediction works well,in terms of e?ciently coding the wavelet coe?cients,due to the statistical characteristics of subbands at various resolutions,and due to the scale-invariance of edges in high frequency subbands of similar orientation.Various extensions of zerotree quantization,such as[3,9],have been pro-posed ever since its introduction.

Wavelet packets[1]were developed in order to adapt the underlying wavelet bases to the contents of a signal.The basic idea is to allow non-octave subband decomposition to adaptively select the best basis for a particular signal.Results from various image cod-ing schemes based on wavelet packets show that they are particularly good in coding images with oscilla-tory patterns,a special form of texture.While wavelet packet bases are well adapted to the corresponding signal(image),one loses the parent-o?spring depen-dencies,or the spatial orientation trees,as de?ned in [8,7].

In this work,we address the following question: can the zerotree quantization be applied to wavelet packet transformed images?The question is valid since one does not generally observe as much self-similarities among the wavelet packet subbands as among the wavelet subbands.Moreover,even if there does exist self-similarity among wavelet packet sub-bands,the question arises:how would the spatial ori-entation trees,or zerotrees,be de?ned in order to pre-dict the insigni?cance of corresponding wavelet pack-ets at a?ner scale,given a wavelet packet at a coarser scale?The issue was addressed partially by Xiong et al.in[10].In their work,however,the tree decompo-sition was restricted not to have a basis causing the parenting con?ict,a problem described in the next sec-tion.We present a solution to this problem and de?ne a set of rules to construct the zerotree structure for a given wavelet packet geometry,thus o?ering a general structure for an arbitrary wavelet packet decomposi-tion.This generalized zerotree structure is termed as the compatible zerotree for reasons mentioned in the next section.The new tree structure provides an e?-cient way of encoding the wavelet packet coe?cients. We combine the idea of zerotree quantization with wavelet packet transforms for image coding purposes. 2Compatible Zerotree Quantization The wavelet packet basis[1]is adaptively selected in order to tailor the representation to the contents of a signal(an image,in our case).The nodes in a full subband tree(or short-term Fourier transform, namely STFT,tree)are pruned following a series of split/merge decisions using certain criterion(see[2] for entropy-based best basis selection and[6]for op-timizing the best basis from a rate-distortion view-point).Suppose the best basis has been selected us-

ing one of these methods.The issue is how to organize the spatial orientation trees so as to exploit the self-similarities,if any,among the subbands.The basis selected by any of the above methods does not,in gen-eral,yield the parent-o?spring relationships like those in wavelet subbands.Moreover,there can be an in-stance in the wavelet packet tree where one or more of the child nodes are at a coarser scale than the parent node.This results in the association of each coe?cient of such a child node to multiple parent coe?cients,in the parent node,giving rise to a parenting con?ict. To make the point clear,let us consider the segmen-tation shown in Figure1,for a3-level wavelet packet transform.The nodes C1,C2,C3,and C4at a coarser scale are children of the node P at a?ner scale.The problem with such a situation is that there are four candidates in P claiming the parenthood of the set of four coe?cients belonging to the four children nodes. In[10],the best basis was selected in such a way that whenever a con?ict like this arises,the four children are merged so as to resolve the con?ict.This subopti-mal approach constrains selection of the best basis at the loss of the freedom of adapting the wavelet packet basis to the contents of a particular

signal.

Figure1:Sample segmentation in a3-level wavelet packet decomposition and the parent-o?spring dependencies for compatible zerotree originating from T1.

We organize the zerotree structure,called compat-ible zerotrees,dynamically so that there is no restric-tion on selection of the wavelet packet basis(we call these the compatible zerotrees,since they are gener-ated taking into account both the scale and orientation compatibility).It is to be noted that the compatible zerotrees di?er from the spatial orientation trees of[7] in the sense that nodes of a compatible zerotree rep-resent a full subband,rather than one or more coe?-cients.We utilize the compatible zerotrees to?nd the coe?cients which are zerotree roots,for a given thresh-old.A set of rules is de?ned to construct the compati-ble zerotrees so that the overall zerotree structure can be constructed for any arbitrary wavelet packet basis. The only assumption made is that the basis has its lowest frequency bands at the coarsest scale.This is based upon the fact that a signi?cant amount of the signal energy is concentrated in the lowest frequency subbands,which cannot be merged by any of the tree pruning algorithms.

Let R denotes the node representing the lowest fre-quency subband,situated in the top-left corner of a conventional subband decomposed image.Then R represents the root node of overall compatible ze-rotree.It has three children(T1,T2,and T3as shown in Figure1)which represent the coarsest scale high-frequency subbands.These children are themselves root nodes of three compatible zerotrees with di?erent global orientations;horizontal,vertical,and diagonal respectively.These zerotrees are generated in a re-cursive manner(only once for a given wavelet packet basis)using the following set of rules,each of them applied to nodes with similar global orientation.

a)If a node P is followed by four nodes C1,C2,C3,

and C4(at the same scale),then P is declared to be the parent of all these four nodes.

b)If four subbands P1,P2,P3,and P4at a coarser

scale are followed by four subbands C1,C2,C3, and C4at immediately next?ner scale,then node P i is declared to be the parent of node C i(for i=1,2,3,4).

c)If a node P at a coarser scale is followed only by

a node C at the immediately next?ner scale(like

in a wavelet transform),the node P is declared as a parent of C.

d)If a node P is at a?ner scale than four of its

children,say C1,C2,C3,and C4,then P is disre-garded as being the parent of all these nodes and all this bunch is moved up in the tree.

Let us consider the segmentation shown in Figure1to explain these rules.The construction of?nal compat-ible zerotrees proceeds in two steps.In the?rst step, the primary compatible zerotrees T1,T2,and T3are constructed using rules a,b,and c,as shown in Figure 2.In the second step,the overall tree is re-organized (as shown in Figure3)using rule d,in order to resolve the parenting con?ict under node P.This rule?rst identi?es nodes with the parenting con?icts and when such nodes are found,the whole bunch(consisting of C1,C2,C3,and C4)is plucked from its current po-sition in the tree.The algorithm then climbs up the

tree to look for an appropriate node,a compatible an-cestor at the nearest scale and having the nearest ori-entation,and glues the bunch under this newly found compatible parent.The parent-o?spring dependencies for the primary compatible zerotree T1are shown in Figure1.For more details of the algorithm to con-struct the compatible zerotrees,please refer to[5].

Given an arbitrarily segmented wavelet packet ba-sis,the compatible zerotrees are constructed using the set of rules described as above.In order to be able to make predictions for wavelet packet coe?cients at ?ner scale subbands,the compatible zerotree hypothe-sis is de?ned as follows:If a wavelet packet coe?cient of a node from the compatible zerotree is insigni?cant, it is more likely that the wavelet packet coe?cients at similar spatial locations in all the descendent nodes of the same compatible zerotree will be insigni?cant as well.

We tested the success of compatible zerotree hy-pothesis,as de?ned above,for wavelet packets.The plots of wavelet packet coe?cients’amplitude against the coe?cient indices for the wavelet packet decompo-sition,using the entropy-based basis selection criterion as in[4],of a512×512Barbara image are shown in Figures4and5.The amplitude axis in both plots was restricted to±1000to facilitate the display of smaller coe?cients.While the subbands were arranged in an increasing frequency order for the plot in Figure4,the plot in Figure5refers to the subbands as organized in the compatible zerotrees.The three families of pri-mary compatible zerotrees T1,T2,and T3are clearly visible in the latter of these plots showing that the new arrangement was successful in isolating the coef-?cients of similar orientation in a hierarchy to be used for prediction in a top-down order.

3The Coder Algorithm

Once the compatible zerotrees have been generated, based upon knowledge of the best basis,the encod-ing takes place by repeatedly running the detection stage and the?ne-tuning stage until the bit budget is expired.Our algorithm requires only one list of detected coe?cients(LDC)to be maintained,as op-posed to two(three)lists kept by the EZW(SPIHT). The decoder?rst reads geometry of the best basis and generates the compatible zerotrees,and then proceeds by entropy decoding and interpreting the codewords (see[5]for more details of the algorithm).

4Experiments and Conclusions The idea of compatible zerotree quantization was coupled with the wavelet packet transform for pro-gressive image coding and its performance was tested against the fast adaptive wavelet packet(FAWP)[4] image codec algorithm.A comparison of the peak sig-nal to noise ratio(PSNR)achieved by CZQ and FAWP for three standard512×512images encoded at tar-get bit rates of0.25and0.10bits per pixel(bpp)is presented in Table1.While being relatively faster,by a factor ranging from two to four,than the bitplane coding of FAWP,the CZQ performs comparably well. We note that the e?ectiveness of zerotree quantization depends strongly upon the scale-invariance of edges among subbands of similar global orientation.The success of prediction of?ner scale coe?cients(set of all descendents D i at similar spatial location)based upon a given coe?cient i at a coarser scale is a func-tion of the conditional probability of D i being insigni?-cant,given i is insigni?cant.We compared the number of zerotree root nodes detected,for various values of threshold,both for wavelet and wavelet packet bases. It was observed that the probability of detection of the zerotree root nodes in a wavelet decomposition is far greater than that in a wavelet packet decomposition.

It is important to note here that the wavelet packet basis was selected by simply using?rst-order entropy as a criterion for the split/merge decisions.The coe?-cients of basis were,therefore,imposed to be zerotree quantized.As opposed to wavelets,the wavelet packet basis might not necessarily produce coe?cients that help towards success of the zerotree hypothesis(that is,produce more zerotrees).Figure6shows the geom-etry of wavelet packet basis selected for the512×512 Barbara image.In fact,we found that using the en-tropy as a criterion for the best basis selection might result into many coarse scale high frequency subbands (whose coe?cients represent oscillatory patterns in some parts of the image),as is clear from basis ge-ometry in Figure6.It is the encoding of coe?cients in these types of subbands which takes considerable amount of the bit budget for the following reason.If a coe?cient somewhere at the bottom of a compati-ble zerotree is found to be signi?cant,the signi?cance of all the corresponding coe?cients in sibling and the parent nodes needs to be encoded as well,even if some or most of them are insigni?cant.Our future work aims to look at the methods of optimizing the selec-tion of best basis using a criterion which results into optimal number of zerotrees and optimal distortion value,given the bit budget.Moreover,the ordering of wavelet packet coe?cients with respect to increas-ing frequency(that is,decaying magnitude)within the compatible zerotrees will provide a gain in the coding performance,by increasing the e?ciency of arithmetic coder to encode the zerotree codewords.

Figure 2:The overall compatible zerotree structure com-prising of the three primary compatible zerotrees T 1,T 2,and T 3;each node represents a whole wavelet packet sub-band,and the node radius is directly proportional to the support of wavelet packets at that transform

level.

Figure 3:The overall compatible zerotree structure,after

re-organization to resolve the parenting con?icts;the edge labels depict the rules used to generate the links between parent and the children

nodes.

Figure 4:Plot of wavelet packet coe?cients’amplitude

versus coe?cient indices for the wavelet packet decompo-sition of 512×512Barbara image;the subbands were ar-ranged in an increasing frequency

order.

Figure 5:Plot of wavelet packet coe?cients’amplitude

versus coe?cient indices for the wavelet packet decom-position of 512×512Barbara image;the subbands were organized in compatible zerotrees with the help of rules mentioned in Section

2.

Figure 6:Wavelet packet basis selected for the 512×512

Barbara image using ?rst-order entropy as selection crite-rion.

Rate (bpp)

FA WP

Fingerprint

26.68

0.10

23.81Goldhill

29.19

0.10

27.54

Lena

31.88

0.10

29.33

Acknowledgement

This work was supported in part by DARPA/AFOSR under Grant F49620-97-1-0011.

References

[1]R.R.Coifman and Y.Meyer,Othornormal wave

packet bases,preprint,Dept.of Mathematics, Yale University,New Haven(1990).

[2]R.R.Coifman and M.V.Wickerhauser,Entropy-

based algorithms for best basis selection,IEEE Trans.on Information Theory38(1992),no.2, 713–718.

[3]M.E?ros,Zerotree design for image compression:

Toward weighted universal zerotree coding,IEEE Intl.Conf.on Image Processing,November1997.

[4]F.G.Meyer, A.Z.Averbuch,J-O.Str¨o mberg,

and R.R.Coifman,Fast wavelet packet image compression,Data Compression Conference-DCC’98,1998.

[5]N.M.Rajpoot,F.G.Meyer,and R.R.Coifman,

Wavelet packet image coding using compatible ze-rotree quantization,Technical Report,Dept.of Computer Science,Yale University,New Haven (1999).

[6]K.Ramchandran and M.Vetterli,Best wavelet

packet bases in a rate-distortion sense,IEEE Trans.on Image Processing(1993),160–175. [7]A.Said and W.A.Pearlman,A new fast and ef-

?cient image codec based on set partioning in hi-erarchical trees,IEEE Trans.on Circ.&Sys.for Video Tech.6(1996),243–250.

[8]J.M.Shapiro,Embedded image coding using ze-

rotrees of wavelet coe?cients,IEEE Trans.on Signal Processing(1993),3445–3462.

[9]Z.Xiong,O.Guleryuz,and M.T.Orchard,Em-

bedded image coding based on DCT,VCIP’97,San Jose,CA,Feb.1997.

[10]Z.Xiong,K.Ramchandran,and M.T.Or-

chard,Wavelet packet image coding using space-frequency quantization,IEEE Trans.on Image Processing7,N.6(1998),892–898.

介词in,on.at,for.with,by,of的基本用法

介词用法知多少 介词是英语中最活跃的词类之一。同一个汉语词汇在英语中可译成不同的英语介词。例如汉语中的“用”可译成:(1)用英语(in English);(2)用小刀(with a knife);(3)用手工(by hand);(4)用墨水(in ink)等。所以,千万不要以为记住介词的一两种意思就掌握了这个介词的用法,其实介词的用法非常广泛,搭配能力很强,越是常用的介词,其含义越多。下面就简单介绍几组近义介词的用法及其搭配方法。 一. in, to, on和off在方位名词前的区别 1. in表示A地在B地范围之内。如: Taiwan is in the southeast of China. 2. to表示A地在B地范围之外,即二者之间有距离间隔。如: Japan lies to the east of China. 3. on表示A地与B地接壤、毗邻。如: North Korea is on the east of China. 4. off表示“离……一些距离或离……不远的海上”。如: They arrived at a house off the main road. New Zealand lies off the eastern coast of Australia. 二. at, in, on, by和through在表示时间上的区别 1. at指时间表示: (1)时间的一点、时刻等。如: They came home at sunrise (at noon, at midnight, at ten o’clock, at daybreak, at dawn). (2)较短暂的一段时间。可指某个节日或被认为是一年中标志大事的日子。如: He went home at Christmas (at New Year, at the Spring Festival, at night). 2. in指时间表示: (1)在某个较长的时间(如世纪、朝代、年、月、季节以及泛指的上午、下午或傍晚等)内。如: in 2004, in March, in spring, in the morning, in the evening, etc (2)在一段时间之后。一般情况下,用于将来时,谓语动词为瞬间动词,意为“在……以后”。如: He will arrive in two hours. 谓语动词为延续性动词时,in意为“在……以内”。如: These products will be produced in a month. 注意:after用于将来时间也指一段时间之后,但其后的时间是“一点”,而不是“一段”。如: He will arrive after two o’clock. 3. on指时间表示: (1)具体的时日和一个特定的时间,如某日、某节日、星期几等。如: On Christmas Day(On May 4th), there will be a celebration. (2)在某个特定的早晨、下午或晚上。如: He arrived at 10 o’clock on the night of the 5th. (3)准时,按时。如: If the train should be on time, I should reach home before dark. 4. by指时间表示: (1)不迟于,在(某时)前。如:

初中英语介词用法归纳总结

初中英语介词用法归纳总结 常用介词基本用法辨析 表示方位的介词:in, to, on 1. in 表示在某地范围之内。 Shanghai is/lies in the east of China. 上海在中国的东部。 2. to 表示在某地范围之外。 Japan is/lies to the east of China. 日本位于中国的东面。 3. on 表示与某地相邻或接壤。 Mongolia is/lies on the north of China. 蒙古国位于中国北边。 表示计量的介词:at, for, by 1. at 表示“以……速度”“以……价格”。 It flies at about 900 kilometers an hour. 它以每小时900公里的速度飞行。 I sold my car at a high price. 我以高价出售了我的汽车。 2. for 表示“用……交换,以……为代价”。 He sold his car for 500 dollars. 他以五百元把车卖了。

注意:at表示单价(price) ,for表示总钱数。 3. by 表示“以……计”,后跟度量单位。 They paid him by the month. 他们按月给他计酬。 Here eggs are sold by weight. 在这里鸡蛋是按重量卖的。 表示材料的介词:of, from, in 1. of 成品仍可看出原料。 This box is made of paper. 这个盒子是纸做的。 2. from 成品已看不出原料。 Wine is made from grapes. 葡萄酒是葡萄酿成的。 3. in 表示用某种材料或语言。 Please fill in the form in pencil first. 请先用铅笔填写这个表格。They talk in English. 他们用英语交谈。 表示工具或手段的介词:by, with, on 1. by 用某种方式,多用于交通。 I went there by bus. 我坐公共汽车去那儿。 2. with表示“用某种工具”。

英语介词用法详解

英语常用介词用法与辨析 ■表示方位的介词:in, to, on 1. in 表示在某地范围之内。如: Shanghai is/lies in the east of China. 上海在中国的东部。 2. to 表示在某地范围之外。如: Japan is/lies to the east of China. 日本位于中国的东面。 3. on 表示与某地相邻或接壤。如: Mongolia is/lies on the north of China. 蒙古国位于中国北边。 ■表示计量的介词:at, for, by 1. at表示“以……速度”“以……价格”。如: It flies at about 900 kilometers a hour. 它以每小时900公里的速度飞行。 I sold my car at a high price. 我以高价出售了我的汽车。 2. for表示“用……交换,以……为代价”。如: He sold his car for 500 dollars. 他以五百元把车卖了。 注意:at表示单价(price) ,for表示总钱数。 3. by表示“以……计”,后跟度量单位。如: They paid him by the month. 他们按月给他计酬。 Here eggs are sold by weight. 在这里鸡蛋是按重量卖的。 ■表示材料的介词:of, from, in 1. of成品仍可看出原料。如: This box is made of paper. 这个盒子是纸做的。 2. from成品已看不出原料。如: Wine is made from grapes. 葡萄酒是葡萄酿成的。 3. in表示用某种材料或语言。如: Please fill in the form in pencil first. 请先用铅笔填写这个表格。 They talk in English. 他们用英语交谈(from 。 注意:in指用材料,不用冠词;而with指用工具,要用冠词。请比较:draw in penc il/draw with a pencil。 ■表示工具或手段的介词:by, with, on 1. by用某种方式,多用于交通。如by bus乘公共汽车,by e-mail. 通过电子邮件。

The way常见用法

The way 的用法 Ⅰ常见用法: 1)the way+ that 2)the way + in which(最为正式的用法) 3)the way + 省略(最为自然的用法) 举例:I like the way in which he talks. I like the way that he talks. I like the way he talks. Ⅱ习惯用法: 在当代美国英语中,the way用作为副词的对格,“the way+ 从句”实际上相当于一个状语从句来修饰整个句子。 1)The way =as I am talking to you just the way I’d talk to my own child. He did not do it the way his friends did. Most fruits are naturally sweet and we can eat them just the way they are—all we have to do is to clean and peel them. 2)The way= according to the way/ judging from the way The way you answer the question, you are an excellent student. The way most people look at you, you’d think trash man is a monster. 3)The way =how/ how much No one can imagine the way he missed her. 4)The way =because

介词by用法归纳-九年级

页脚.

. . 教学过程 一、课堂导入 本堂知识是初中最常见的介词by的一个整理与总结,让学生对这个词的用法有一个系统的认识。页脚.

. . 二、复习预习 复习上一单元的知识点之后,以达到复习的效果。然后给学生一些相关的单选或其他类型题目,再老师没有讲解的情况下,让学生独立思考,给出答案与解释,促进学生发现问题,同时老师也能发现学生的盲点,并能有针对性地进行后面的讲课。 页脚.

. . 三、知识讲解 知识点1: by + v.-ing结构是一个重点,该结构意思是“通过……,以……的方式”,后面常接v.-ing形式,表示“通过某种方式得到某种结果”,即表示行为的方式或手段。 I practice speaking English by joining an English-language club. 我通过加入一个英语语言俱乐部来练习讲英语。 Mr Li makes a living by driving taxis.先生靠开出租车为生。 页脚.

. . 页脚. 介词by + v.-ing 结构常用来回答How do you...?或How can I...?之类的问题。 —How do you learn English? 你怎样学习英语呢? —I learn English by reading aloud. 我通过大声朗读来学英语。 —How can I turn on the computer? 我怎样才能打开电脑呢? —By pressing this button. 按这个按钮。 知识点2:by 是个常用介词,其他用法还有: 1【考查点】表示位置,意思是“在……旁边”,“靠近……”,有时可与beside互换。 The girls are playing by (beside) the lake. 女孩们正在湖边玩。 此时要注意它与介词near有所不同,即by 表示的距离更“近”。比较: He lives by the sea. 他住在海滨。 He lives near the sea. 他住在离海不远处。

The way的用法及其含义(二)

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不对。 Theway(that ,in which)you’re doingit is comple tely crazy.你这么个干法,简直发疯。 Weadmired him for theway inwhich he facesdifficulties. Wallace and Darwingreed on the way inwhi ch different forms of life had begun.华莱士和达尔文对不同类型的生物是如何起源的持相同的观点。 This is the way(that) hedid it. I likedthe way(that) sheorganized the meeting. 3.theway(that)有时可以与how(作“如何”解)通用。例如: That’s the way(that) shespoke. = That’s how shespoke.

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near:近的,不远的 by:在...的旁边,比near的距离要近 between:在两者之间 among:在三者或者更多的之中 around:环绕,在...的周围,在....的四周 in front of:在...的前面 behind:在...后边 in:在..之内,用于表示静止的位置 into:进入 out of :和into一样,也表示有一定的运动方向 along:沿着 across:横过平面物体 through:贯通,通过 to :达到..地点目的地或方向 for:表示目的,为了..... from:从...地点起 其他介词 with:和..在一起; 具有,带有; 用某种工具或方法 in:表示用什么材料例如:墨水,铅笔等或用什么语言。表示衣着.声调特点时,不用with而用in。 by:通过...方法,手段 of:属于...的,表示...的数量或种类 from:来自某地,某人,以...起始 without:没有,是with的反义词 like :像...一样

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way 用法

表示“方式”、“方法”,注意以下用法: 1.表示用某种方法或按某种方式,通常用介词in(此介词有时可省略)。如: Do it (in) your own way. 按你自己的方法做吧。 Please do not talk (in) that way. 请不要那样说。 2.表示做某事的方式或方法,其后可接不定式或of doing sth。 如: It’s the best way of studying [to study] English. 这是学习英语的最好方法。 There are different ways to do [of doing] it. 做这事有不同的办法。 3.其后通常可直接跟一个定语从句(不用任何引导词),也可跟由that 或in which 引导的定语从句,但是其后的从句不能由how 来引导。如: 我不喜欢他说话的态度。 正:I don’t like the way he spoke. 正:I don’t like the way that he spoke. 正:I don’t like the way in which he spoke. 误:I don’t like the way how he spoke. 4.注意以下各句the way 的用法: That’s the way (=how) he spoke. 那就是他说话的方式。 Nobody else loves you the way(=as) I do. 没有人像我这样爱你。 The way (=According as) you are studying now, you won’tmake much progress. 根据你现在学习情况来看,你不会有多大的进步。 2007年陕西省高考英语中有这样一道单项填空题: ——I think he is taking an active part insocial work. ——I agree with you_____. A、in a way B、on the way C、by the way D、in the way 此题答案选A。要想弄清为什么选A,而不选其他几项,则要弄清选项中含way的四个短语的不同意义和用法,下面我们就对此作一归纳和小结。 一、in a way的用法 表示:在一定程度上,从某方面说。如: In a way he was right.在某种程度上他是对的。注:in a way也可说成in one way。 二、on the way的用法 1、表示:即将来(去),就要来(去)。如: Spring is on the way.春天快到了。 I'd better be on my way soon.我最好还是快点儿走。 Radio forecasts said a sixth-grade wind was on the way.无线电预报说将有六级大风。 2、表示:在路上,在行进中。如: He stopped for breakfast on the way.他中途停下吃早点。 We had some good laughs on the way.我们在路上好好笑了一阵子。 3、表示:(婴儿)尚未出生。如: She has two children with another one on the way.她有两个孩子,现在还怀着一个。 She's got five children,and another one is on the way.她已经有5个孩子了,另一个又快生了。 三、by the way的用法

介词in重要用法归纳

后”: I ' ll see you aga in with in three days. 3 I ' ll see you again after three days. 3 Look, there ' s a hole on the wall.介词in 重要用法归纳 介词in 用法比较复杂,以下几点比较重要,须引起注意: 1.表示时间,表示“在……后”,注意它与after 的区别:虽然两者均可与一段时间连用, 表示多久之后,但in 以现在时间为起点,表示从现在起多久以后,通常用于将来时态或 含有将来意味的句子;而 after 则以过去或将来时间为起点,表示从那以后。如: I ' II come back in five minutes. 我5分钟后就回来。(以现在时间为起点) He came back after five minu tes. 5 分钟后他就回来了。(以过去时间为起点) 但是,若after 后接的不是一 “段”时间,而是一 “点”时间,则完全可以现在时间为起点。 如: I ' ll come back after five o ' clock. 我 5点钟以后回来。 不过,在现代英语中,以上规则有时被打破。如: I may come after a day or two. 我可能过一两天会来。 Wang Bing is leavi ng the USA after two days. 两天后王兵要离开美国。 2.类似in three days 这样的短语,有时含义不易确定,因为它既可表示“ 3天内”, 也可表示“ 3天后”,大致可以这样区分:若与延续性动词连用,则表示“ 3天内”,若与 非延续性动词连用,则表示“ 3天后”。如: He lear nt En glish in three weeks. 他在3周内学会了英语。 The train will arrive in a few minu tes. 火车过几分钟就到。 但语言的实际并不完全是这样,有时需视具体的上下文或语境来确定。如: We should be able to complete the work in five days. 我们应该能在 5天内完成这工 作。 为了明确语义,有时人们就分别用 within 和 after 来表示“在……内”和“在 3. 表地点、位置、范围、空间等,注意不要混淆 in 与on 的用法。如: 瞧, 墙上有个 洞。 天内我再来看你。 天后我再来看你。 误: 正: Look, there s a hole in the wall.

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