1、. 城建學(xué)院本科畢業(yè)設(shè)計(jì)(論文)開題報(bào)告 題目： 圖像壓縮算法的研究課 題 類 型： 論文學(xué) 生 姓 名： 呂建輝 學(xué) 號(hào)： 093410130專 業(yè) 班 級(jí)： 0934101系 別： 電氣系指 導(dǎo) 教 師： 石磊開 題 時(shí) 間： 2014年3月 2014 年 04 月 10日一、畢業(yè)設(shè)計(jì)容及研究意義設(shè)計(jì)的容：本論文的主要研究容是圖像壓縮技術(shù)。具體框架是首先介紹了圖像壓縮的根本原理以及其相關(guān)壓縮方法分類等理論知識(shí)，并且說明了對(duì)圖像進(jìn)展壓縮的必要性與重要性，然后針對(duì)目前圖像壓縮現(xiàn)狀和開展趨勢(shì)，著重介紹了小波變換，并以其為根底來進(jìn)展數(shù)字圖像的壓縮處理，這也許會(huì)成為圖像數(shù)據(jù)壓縮的主要技術(shù)之一。接著又

2、根據(jù)相關(guān)知識(shí)編寫了一些簡(jiǎn)單的圖像處理程序，對(duì)前面的理論進(jìn)展試驗(yàn)、分析、論證。最后，對(duì)整篇論文進(jìn)展總結(jié)，發(fā)現(xiàn)自身研究的缺乏，并展望其未來開展前景研究意義：圖像信息給人們以直觀、生動(dòng)的形象，正成為人們獲取外部信息的重要途徑。然而，數(shù)字圖像具有極大的數(shù)據(jù)量，在目前的計(jì)算機(jī)系統(tǒng)的條件下，要想實(shí)時(shí)處理，假設(shè)圖像信息不經(jīng)過壓縮，則會(huì)占用信道寬，是傳輸本錢變得昂貴，傳輸速率變慢。這對(duì)圖像存儲(chǔ)、傳輸及使用都非常不利，同時(shí)也阻礙了人們對(duì)圖像的有效獲取和使用。另外，伴隨著計(jì)算機(jī)科學(xué)技術(shù)的開展，圖像壓縮技術(shù)在通信系統(tǒng)和多媒體系統(tǒng)中的重要性也越來越高，在我們的學(xué)習(xí)、生產(chǎn)、生活以及國(guó)防事物中等的作用越來越顯著。為此，人

3、們給予了圖像壓縮技術(shù)廣泛的關(guān)注，如何用盡量少的數(shù)據(jù)量來表示圖像信息，即對(duì)圖像進(jìn)展壓縮，越來越成為圖像研究領(lǐng)域的重點(diǎn)課題。二、畢業(yè)設(shè)計(jì)研究現(xiàn)狀和開展趨勢(shì)研究現(xiàn)狀：第一代圖像壓縮編碼的研究工作是從上個(gè)世紀(jì)50年代提出電視信號(hào)數(shù)字后開場(chǎng)的，至今己有60多年的歷史。主要是基于信息論的編碼方法，壓縮比小。1966年比照分析了差分編碼調(diào)制(DPCM)和脈沖編碼調(diào)制(PCM)并提出了用于電視的實(shí)驗(yàn)數(shù)據(jù)，1969行了線性預(yù)測(cè)編碼的實(shí)際實(shí)驗(yàn)。同年舉行首屆圖像編碼會(huì)(PictureCodiSymP0sium)，在這次會(huì)議之后，圖像壓縮編碼算法的研究有了很大進(jìn)展。由于DCT壓縮算法具有編碼效果較好、運(yùn)算復(fù)雜度適中等

4、優(yōu)點(diǎn)，目前己經(jīng)成為國(guó)際圖像編準(zhǔn)(JPEG)的核心算法。為了克制第一代圖像壓縮編碼存在的壓縮比小、圖像復(fù)原質(zhì)量不理想等1985年Kunt等人充分利用人眼視覺特性提出了第二代圖像壓縮編碼的概念。上世紀(jì)80年代中后期，人們相繼提出了在多分辨率下表示圖像的方案，主要方子帶壓縮編碼、金字塔壓縮編碼等。這些方法均在不同程度上有如下優(yōu)點(diǎn):多分辨率的信號(hào)表示有利于圖形信號(hào)的漸輸，不同分辨率的信號(hào)占用不同的頻帶，便于引入視覺特性。1987年，Mallat次巧妙地將計(jì)算機(jī)視覺領(lǐng)域的多尺度分析思想引入到小波變換中，統(tǒng)一了在之前各種小波的構(gòu)造方法之后，他又研究了小波變換的離散形式，并將相應(yīng)的法應(yīng)用于圖像的分解與重構(gòu)中

5、，為隨后的小波圖像壓縮編碼奠定了理論根底。1988年Barnsly和S1an共同提出了分形圖像編碼壓縮方案，之后，各國(guó)學(xué)者提出各種各樣的改良方法，從而掀起了分形圖像編碼的新高潮。但由于在分形壓縮編碼過程中，運(yùn)算量大，從而造成編碼時(shí)間過長(zhǎng)，且提高壓縮比同減小失真度之間的矛盾始終存在，從而局限了它的實(shí)用性。上個(gè)世紀(jì)90年代后，又取得了一系列圖像壓縮編碼研究的階段性新成果，基于零樹的編碼法首先由和G.Knoes提出，其特點(diǎn)是根據(jù)小波系數(shù)在同方向子帶中的相似性，即假設(shè)一個(gè)小波系數(shù)較小，則很可能高一級(jí)(頻率更高)同方向子帶中相應(yīng)位置的小波系數(shù)也較小，利用一種稱為小波樹的樹形構(gòu)造來組織小波系數(shù)，使其能方便

6、地去除頻域和空間域中的相關(guān)性。接著Shapir結(jié)合比特平面編碼方法設(shè)計(jì)了更好的零樹編碼方法，Shapri提出的嵌入式零樹小波算法是迄今為止最有效的方法，它有效地利用了小波系數(shù)的特性，實(shí)現(xiàn)了圖像的可分級(jí)編碼，但是不同程度地存在算法時(shí)間復(fù)雜度和空間復(fù)雜度過高的弱點(diǎn)。目前，小波變換的圖像壓縮編碼算法已成為圖像壓縮研究領(lǐng)域的一個(gè)主要方向，基于小波變換的圖像編碼技術(shù)正逐步顯示出它的優(yōu)越性，其中小波變換己被JPEG-2000國(guó)際標(biāo)準(zhǔn)采用。開展趨勢(shì)：隨著數(shù)字化技術(shù)的迅速開展，數(shù)字圖像也被越來越多的運(yùn)用在我們的日常學(xué)習(xí)、生活、工作當(dāng)中，圖像壓縮技術(shù)將會(huì)非常的重要。從國(guó)際數(shù)據(jù)壓縮技術(shù)的開展尤其是MPEG的開展可

7、以看出，基于容的圖像壓縮編碼方法是未來編碼的開展趨勢(shì)。它不僅能滿足進(jìn)一步獲得更大的圖像數(shù)據(jù)壓縮比的要求，而且能夠?qū)崿F(xiàn)人機(jī)對(duì)話的功能。另外，任意形狀物體的模型建立的關(guān)鍵問題還沒有解決，這嚴(yán)重影響其應(yīng)用的廣泛性。因此，圖像編碼將朝著多模式和跨模式的方向開展。通過元數(shù)據(jù)進(jìn)展編碼也是今后編碼的開展方向。元數(shù)據(jù)是指詳細(xì)的描述音/視頻信息的根本元素，利用元數(shù)據(jù)來描述音視頻對(duì)象的同時(shí)也就完成了編碼，因?yàn)榇藭r(shí)編碼的對(duì)象是圖像的一種描述而不再是圖像本身。從另一個(gè)角度來說，進(jìn)一步提高壓縮比，提高碼流的附屬功能碼流容的可訪問性、抗誤碼能力、可伸縮性等也將是未來的編碼的兩個(gè)開展方向。三、畢業(yè)設(shè)計(jì)研究方案及工作方案1、

8、研究方案此次論文撰寫擬從圖像數(shù)據(jù)壓縮的必要性出發(fā)，闡述本課題的研究義，然后簡(jiǎn)單介紹了圖像壓縮編碼技術(shù)的開展現(xiàn)狀，最后對(duì)本文的主要工作以及各章的容編排做了說明。接下來對(duì)數(shù)字圖像壓縮的必要性、重要性以及現(xiàn)今國(guó)外對(duì)于這一技術(shù)領(lǐng)域的研究現(xiàn)狀介紹開場(chǎng)，進(jìn)而系統(tǒng)并簡(jiǎn)明的述說圖像壓縮理論知識(shí)。緊接著將對(duì)為何要選用小波變換為根底，來進(jìn)展數(shù)字圖像的壓縮處理進(jìn)展具體且詳細(xì)的論述，并且介紹了小波變換對(duì)靜止的圖像進(jìn)展編碼的技術(shù)，闡述了Matlab算法，最后附上相關(guān)程序，通過實(shí)驗(yàn)來驗(yàn)證本論文所選方法的優(yōu)越性。最后是對(duì)此次論文的總結(jié)。具體有以下幾方面的工作：1、介紹圖像及圖像壓縮的相關(guān)知識(shí)，弄清楚圖像定義、根本概念及壓縮

9、編碼的根本過程，并且重點(diǎn)討論幾種傳統(tǒng)的、在圖像壓縮中被廣泛采用的編碼方法及其根本原理。2、通過分析比擬小波變換和傳統(tǒng)變換方法，發(fā)現(xiàn)小波變換在圖像壓縮技術(shù)領(lǐng)域的優(yōu)越性。同時(shí)，從小波基的選擇、原始信號(hào)的邊界延拓、小波系數(shù)的量化、熵編碼、小波分解/重構(gòu)級(jí)數(shù)來逐步分析小波編碼的根本思想、理論。3、量化和編碼間的關(guān)系是小波變換壓縮的關(guān)鍵所在。本論文中將用EZW與SPIHT算法來處理這種關(guān)系，即研究該算法的主要思想、實(shí)現(xiàn)步驟，并闡述、編寫基于Matlab軟件的相關(guān)程序，通過程序的運(yùn)行來驗(yàn)證所用方法的優(yōu)越性。2、重點(diǎn)和難點(diǎn)此次論文的重難點(diǎn)是，對(duì)為何要選用小波變換為根底，來進(jìn)展數(shù)字圖像的壓縮處理進(jìn)展：1要介紹

10、小波變換的背景及根本理論、函數(shù)，其中包括對(duì)于傳統(tǒng)變換方法的局限性對(duì)瞬態(tài)和局部信號(hào)分量的分析、時(shí)頻和空頻局部化的論述，小波變換的分類及其它；2分析小波參數(shù)的選擇及其對(duì)圖像壓縮前后的質(zhì)量的影響，以及怎樣利用小波系數(shù)的分布特點(diǎn)和小波圖像特點(diǎn)，對(duì)系數(shù)進(jìn)展組織和編碼，實(shí)現(xiàn)數(shù)字圖像的壓縮；3介紹兩種經(jīng)典的基于小波變換的圖像壓縮編碼算法即EZW算法和SPIHT算法，并研究其主要思想、具體實(shí)現(xiàn)步驟，同時(shí)，認(rèn)真分析各種算法的優(yōu)點(diǎn)和缺點(diǎn)試圖尋找可以改良的地方。最后闡述了Matlab算法，利用小波變換理論進(jìn)展相關(guān)程序的編寫，通過實(shí)驗(yàn)來驗(yàn)證所選方法的優(yōu)越性。3、工作方案學(xué)生呂建輝專業(yè)電子信息工程起止日期日/月周次 容

11、 進(jìn) 程備 注1承受設(shè)計(jì)的課題，查找相關(guān)參考文獻(xiàn)和資料。2熟悉設(shè)計(jì)的課題，查閱、整理參考文獻(xiàn)和資料3學(xué)習(xí)相關(guān)參考文獻(xiàn)和資料。4理清思路，撰寫開題報(bào)告5開題辯論，對(duì)設(shè)計(jì)課題的容作初步論證6容論證，容改良，容定稿7對(duì)小波變換進(jìn)展研究學(xué)習(xí)8對(duì)小波變換進(jìn)展研究學(xué)習(xí)9對(duì)各種圖像壓縮方法研究學(xué)習(xí)10比擬各種圖像壓縮方法的優(yōu)缺點(diǎn)11熟悉畢業(yè)論文格式、撰寫論文初稿12撰寫論文初稿13完成論文初稿并提交14自我修改畢業(yè)論文15自我修改畢業(yè)論文16根據(jù)教師指導(dǎo)，改善缺乏之處，總體完善17完成論文終稿，提交論文終稿18準(zhǔn)備好自述講稿，打印，參加論文辯論四、主要參考文獻(xiàn):1阮秋琦. 數(shù)字圖像處理學(xué)M. : 電子工業(yè),

12、 20012榮椿. 數(shù)字圖像處理導(dǎo)論M. : 西北工業(yè)大學(xué), 19993.數(shù)字圖像處理M. : 電子工業(yè), 20024鐘誠(chéng).小波變換及其應(yīng)用研究J.中國(guó)科技信息,2008,25玉華.小波變換與工程應(yīng)用M.:科學(xué),19996余松煌，文軍.軍等著.現(xiàn)代圖像信息壓縮技術(shù)M .科學(xué)，19987丹.信息論與編碼M.中國(guó)科學(xué)技術(shù)大學(xué)，20018黃賢武.數(shù)字圖像處理與壓縮編碼技術(shù)M .:電子科技大學(xué)，2009榴梯，明奇.黨長(zhǎng)民等著.實(shí)用數(shù)字圖像處理M .理工大學(xué)出社，1998.10 馬平.數(shù)字圖像處理和壓縮M.電子工業(yè),200711顯東，在銘，軍等著.圖像壓縮標(biāo)準(zhǔn)研究的開展與前景M.中國(guó)工程物研究院信息與電

13、子工程，2003.12.12太怡，吳曉蕓，雙騰等著.基于JPEG國(guó)際標(biāo)準(zhǔn)的圖像壓縮方法的研究J .大學(xué)學(xué)報(bào)，1994，17(5)13AnalogDeviees.ADV-JP2000JPEG2000Co-ProeessorJ.PreliminaryTeehniealData，2001.14TAYLOR W F. The Geometry of puter GraphicsM. Wadsworth Inc, 199215 A.J.Patti, M.I.Sezan A.M.Tekalp. Superresolution Video Reconstruction with Arbitrary Samp

14、ling Lattices and Nonzero Aperture Time. IEEE Trans, 199716 Elad M Feuer A. Restoration of a Single Superresolution Image from Several Blurred Noisy and Undersampled Measured Images. IEEE Trans, 199717 J.K.Paik, A.K.Katsaggelos. Iamge restoration using a modified Hopfield network. J IEEE Transaction

15、s on Image Processing, 1992 18閆陽(yáng),正炳.基于小波變換的圖像壓縮編碼J.現(xiàn)代電子技術(shù),2005，28(3)19王曉輝,朱光喜,朱耀庭.圖像的一種分形特性表示法及其應(yīng)用J.電子學(xué)報(bào),1997,25(l0)20練華,宋寶瑞.基于小波變換的分形圖像編碼J.交通大學(xué)學(xué)報(bào),2004,(4)21兢,路彥和.具有感興趣區(qū)域的靜止圖像壓縮編碼算法研究J.計(jì)算機(jī)應(yīng)用,2005,(6)22JOEL AM,Larsson C,Charilaos C.Region of Interest Coding in JPEG 2000J.Signal rocessing:Imag municat

16、ion,2002,(17)附： 一篇引用的外文文獻(xiàn)Analysis of pression Encoding about Digital ImageYufangGao Yang LiuBeijing University of Posts and Telemunications,Beijing,PRC,100876Abstract :This paper mainly investigate the theory of image pressing encoding,two parts,the technologyand process of encoding,are included.In

17、the technology of encoding,we give a deep study in thetraditional methods and the use of those methods in the image pression,for e*ampleestimation coding,DCT transform,data quantization,entropy coding.Estimation coding lowers thetime relativity of image data.DCT transform lowers the space relativity

18、 of image data.Dataquantization makes use of the redundancy of mentality and vision.Entropy coding brings downthe redundancy of coding.After those process,image data will be effectively pressed.Based on the coding technology,this paper e*amplified MPEG-2 standard discusses the processof the serial o

19、f motion image,which includes frame and field coding mode.This paper particularlye*pounds the field coding of motion pensation bined with DCT transform,introduces thetheory of motion pensation and the count of motion vector.Motion pensation makes better use of relativity of field data and increases

20、the pensation ratio.Key words:estimation codingDCT transform motion pensationmotion estimation MPEG-2IntroductionDigital images have many advantages, but the digital image of the massive amount of data hinders the development of digital image technology. In recent years, image pression coding have m

21、ade rapid development,the sign is International research on image pression coding drawn up a series of pression standards, such as: JPEG, H.26* series, MPEG series。At the same time the development of VLSI technology makes high-performance image coding special chips as possible, which led to the gold

22、en age of digital image munication development.Digital color television image signal monly used ponent encoding ,luminance signal sampling frequency is 13.5MHZ, color difference signals of the sampling frequency 6.75MHZ. After ponent encoded, The rate of which posed of three ponent signals TDM strea

23、m is: 13.5+6.75+6.758=216Mb/s，so the space for digital video Per minute is: 216Mb/s60s/8=1620MB。Such a huge amount of data makes a 650MB CD can only store one minute of video images, even a 10GB hard drive also can not store a few minutes of video images, it is necessary to press image data.In this

24、paper,we investigate the method that using MATLAB Wavelet Transform for pression. Methods: The image was processed by wavelet transform, and then the information of low frenquency was retained and the information of high frenquency was home zero. Results: The quality of the first image pression was

25、high, but the pression ratio was low. The pression ratio of the second time was higher,and the image quality was good. Conclusion: The method is simple, reliable and effective in image pression.With the puter technology and the rapid development of network technology, images, sound and other multime

26、dia information recording, storage, transmission has been digitized, the huge amount of data brought to the storage and transmission of certain difficulties, digital image pression has bee a solution to the problem key technology.Over the last decade ,wavelet theory has bee a new direction in applie

27、d mathematics. As a mathematical tool, wavelet was quickly applied to the image and voice of many other fields. Wavelet transform is a signal of time - scale analysis method, the characteristics of multi-resolution analysis, and in time and frequency domain has the capacity of local signal character

28、istics, a fi*ed window size, its shape variable, time window and frequency window can change the time-frequency localization analysis, that low frequency high frequency resolution and time resolution, the high frequency part of the high time resolution and lower frequency resolution very suitable fo

29、r detection of transient entrainment of the normal signal anomalies and show its ponents, so the microscope known as signal analysis.2, Image pression Coding TheoryCoding process can be summarized as：Original image Mapping transformation Quantizer Entropy Coder data streamMapping transformation redu

30、ces the correlation between image data，Make it more conducive to pression；Quantizer to map the data into a binary digital signal；Entropy code make that appeared on the probability of a large source of symbols assigned to the short code; Small symbol on the probability assigned to a long code, there

31、by reducing redundant data generated code. Data pression is divided into lossless and lossy pression. Lossless pression means that image data after pression can be pletely restored, restored the same image and original image, while lossless pression refers to the pressed image data while maintaining

32、 the characteristics of the original image under the premise of inevitable loss of part of the original image is not important information. The current image based on wavelet transform press gradually replaced the DCT and the other based on the coding technique, a new image pression international Bi

33、aozhun of choice, such as the most advanced image pression standard JPG2000 the core algorithm is wavelet transform.2.1 Wavelet Analysis Principles and MethodsWavelet analysis is currently applied mathematics and engineering disciplines in a fast-growing new field. Wavelet is a small wave, small mea

34、ns it has the Decay; wave refers to its volatility. With the increasing maturity of wavelet theory, wavelet analysis has bee very broad applications. Image processing is an important area of application of wavelet analysis, image processing has bee a useful tool.2.2The principle of wavelet transform

35、 image pressionWavelet transform for image pression the basic idea is:multi-resolutiondepositionof the image, broken down into different space, differentfrequency sub-image, and then pairs the image coefficients are encoded.Wavelet transform coefficient coding is the core for image pression,pression

36、 is the real coefficient quantization pression. Image after wavelet transform wavelet image data generated and the total amount of data equal to theoriginal image, that wavelet transform itself does not have pression. The reason why itused for image pression, because the resulting wavelet image and

37、the original image withdifferent characteristics, and in the image of the energy concentrated in the low frequency part, while the horizontal, vertical and diagonal part of the energy is less; level,vertical anddiagonal part of the characterization of the original image in the horizontal, vertical a

38、nd diagonal part of the edge information, with clear direction characteristics. Called low-frequency part of the image brightness, horizontal, vertical and diagonal part of the known details of the image Therefore, the simplest method is to use wavelet pression to preserve low-frequency part of the

39、high frequency part of the set 0. Original image is first deposed into low frequency and high frequency horizontal ponent L HL1, high-frequency vertical ponent LH1, high-frequency diagonal ponents HH1, and then further depose the low frequency ponent L repeatedly to the desired level of deposition.

40、As the scaling function with low-pass filter (H) the role of the wavelet function has a high pass filter (G), the role of image wavelet deposition for the equivalent of the horizontal and vertical filtering and sub-sampling, the reverse process of the image shall reconstruction 3. 2.3 Image pression

41、 using Matlab programming stepspressed image using wavelet transform under the following three steps: The discrete wavelet transform image is deposed into low frequency and high frequency ponents similar to the level of high-frequency vertical and diagonal details of the high frequency ponent; E*tra

42、ct low frequency, high-frequency part of the set 0; Using the inverse wavelet transform of the reconstructed image .3 ResultsIn this study,we use MATLAB 6.5 programming.Using wavelet deposition to remove the high frequency part of the image while only retaining the low frequency part of the image as

43、 asimple pression method. Function that is used with wavedec2 bior3.7 waveletdeposition of the image layer, then in low frequency coefficients appcoef2 function, and finally quantified with wcodemat function code. The results are as follows:Original imageThe first pressed imageThe second pressed ima

44、geImage size before pressionName Size Bytes Class* 256 256 524288 double arrayGrand total is 65536 elements using 524288 bytesThe first pressed image sizeNameSize Bytes Classca1 128 128 131072 double arrayGrand total is 16384 elements using 131072 bytesAfter the second pressed image sizeName Size By

45、tes Classca2 64 64 32768 double arrayGrand total is 4096 elements using 32768 bytesFrom the above e*perimental results can be seen that the first pression ratio is 27.81% of before pression.The second pression ratio is 8.58% of before pression.Can be seen from the figure that the effect of the two p

46、ression is good, especially the first time the pression is better. The second pressed image darker ,its reason is the loss caused by a large number of low frequency coefficients. It also verified the second pressed greater.4 DiscussionThese results indicate that the image wavelet transform, remove t

47、he high frequency part, to retain low frequency, can be better pressed image data, to a certain pression ratio can guarantee the quality of image processing. In addition, to further improve the image pression, but also integrated the use of a variety of other technologies, in particular data encodin

48、g and decoding algorithms 4.譯文： 數(shù)字圖像信號(hào)壓縮的編碼分析高玉芳，洋郵電大學(xué)電信工程學(xué)院多媒體中心(100876)摘要：本文主要研究圖像壓縮編碼理論，包括兩個(gè)局部容：編碼技術(shù)和編碼流程。在編碼技術(shù)中，我們?cè)敿?xì)介紹了預(yù)測(cè)編碼、DCT變換編碼、數(shù)據(jù)量化、熵編碼的原理及其在圖像壓縮中的應(yīng)用。預(yù)測(cè)編碼減弱了圖像數(shù)據(jù)的時(shí)間相關(guān)性；DCT變換編碼減弱了數(shù)據(jù)的空間相關(guān)性；數(shù)據(jù)量化利用了人眼心理視覺冗余；熵編碼減小了編碼冗余。減小了這些冗余，圖像數(shù)據(jù)將得到有效的壓縮。在編碼技術(shù)根底之上，本文以MPEG-2為例，系統(tǒng)地討論了運(yùn)動(dòng)圖像視頻序列的編碼流程，包括幀編碼模式和幀間編碼模式

49、。其中重點(diǎn)研究了運(yùn)動(dòng)補(bǔ)償幀間預(yù)測(cè)結(jié)合DCT變換的幀間壓縮編碼，分析了運(yùn)動(dòng)補(bǔ)償?shù)脑砗瓦\(yùn)動(dòng)矢量的計(jì)算方法。關(guān)鍵詞：預(yù)測(cè)編碼 DCT 運(yùn)動(dòng)補(bǔ)償 運(yùn)動(dòng)估值 MPEG-21 引言圖像的數(shù)字化有許多優(yōu)點(diǎn)，但數(shù)字圖像的海量數(shù)據(jù)量阻礙了數(shù)字圖像技術(shù)的開展。近年來，圖像壓縮編碼研究取得了飛速開展，其標(biāo)志國(guó)際上圖像壓縮編碼研究成果而制定的一系列壓縮標(biāo)準(zhǔn)，如：JPEG、H.26*系列、MPEG系列。同時(shí)超大規(guī)模集成電路工藝的開展，使得高性能的圖像編碼專用芯片成為可能，從而引來了數(shù)字圖像通信開展的黃金時(shí)代。數(shù)字彩色電視圖像信號(hào)一般采用分量編碼1方式，亮度信號(hào)取樣頻率為13.5MHZ，色差信號(hào)的取樣頻率為6.75MH

50、Z。分量編碼后三個(gè)分量信號(hào)組成的時(shí)分復(fù)用碼流速率為：13.5+6.75+6.758=216Mb/s，則每分鐘數(shù)字視頻所占用的空間為：216Mb/s60s/8=1620MB。這么龐大的數(shù)據(jù)使得一650MB的光盤只能存儲(chǔ)一分鐘的視頻圖像，即使一塊10GB硬盤也存儲(chǔ)不了幾分鐘的視頻圖像，因此必須對(duì)圖像數(shù)據(jù)進(jìn)展壓縮。本文探討利用MATLAB的小波變換進(jìn)展圖像壓縮的方法。方法：對(duì)圖像進(jìn)展小波變換，保存低頻局部，高頻局部置0。結(jié)果：第一次壓縮時(shí)壓縮效果較好，壓縮比擬小，第二次壓縮時(shí)壓縮較大，圖像視覺效果也令人滿意。結(jié)論：本方法是一種簡(jiǎn)單、有效的壓縮方法。隨著計(jì)算機(jī)技術(shù)和網(wǎng)絡(luò)技術(shù)的迅速開展，圖像、聲音等多媒

51、體信息的記錄、存儲(chǔ)、傳輸已經(jīng)數(shù)字化，龐大的數(shù)據(jù)量給存儲(chǔ)和傳輸帶來了一定的困難，數(shù)字圖像的壓縮已成為解決該問題的關(guān)鍵技術(shù)。近十幾年來小波理論的研究己成為應(yīng)用數(shù)學(xué)的一個(gè)新方向。作為數(shù)學(xué)工具，小波被迅速應(yīng)用到圖像和語(yǔ)音分析等眾多領(lǐng)域。小波變換是一種信號(hào)的時(shí)間尺度分析方法，具有多分辨率分析的特點(diǎn)，而且在時(shí)頻兩域都具有表征信號(hào)局部特征的能力，是一種窗口大小固定不變但其形狀可變，時(shí)間窗和頻率窗都可變的時(shí)頻局部化分析方法，即在低頻局部具有較高的頻率分辨率和時(shí)間分辨率，在高頻局部具有較高的時(shí)間分辨率和較低的頻率分辨率，很適合探測(cè)正常信號(hào)中夾帶的瞬態(tài)反?，F(xiàn)象并展示其成分，所以被譽(yù)為信號(hào)分析的顯微鏡2 圖像壓縮編碼原理圖像編碼的過程可以概括為：原始圖像 映射變換 量化器 熵編碼器 碼流映射變換減小了圖像數(shù)據(jù)之間的相關(guān)性，使之更有利于壓縮編碼；量化器將映射數(shù)據(jù)變?yōu)槎M(jìn)制數(shù)字信號(hào)；熵編碼對(duì)信源中出現(xiàn)概率大的符號(hào)賦以短碼，對(duì)出現(xiàn)概率小的符號(hào)賦以長(zhǎng)碼