【正文】 we go through the image pixel by pixel and pare the color of each pixel to its right neighbor, and to its bottom neighbor. If one of these parison results in a too big difference the pixel studied is part of an edge and should be turned to white, otherwise it is kept in black. The fact that we pare each pixel with its bottom and right neighbor es from the fact that images are in two dimensions. Indeed if you imagine an image with only alternative horizontal stripes of red and blue, the algorithms wouldn39。而且大大提高了動手的能力，使我充分體會到了在創(chuàng)造過程中探索的艱難和成功時的喜悅。如果要改變壓縮比，只需要調(diào)整程序中子矩陣的大小即可。小波變換能夠有效地應(yīng)用于圖像數(shù)據(jù)壓縮，從根本上說，其壓縮機理正是體現(xiàn)在小波變換對圖像的多頻段分解恰與人類覺系統(tǒng)的多頻率通道特性相吻合，從而使我們能夠從人類視覺的多通道處理特性上對圖像進行相應(yīng)的壓縮處理。 %改變圖像高度figure,image(ca2)。,0)。39。我們運用Matlab工具箱中的函數(shù)及相關(guān)語法得到如下程序：clear allI=imread(39。,2)。 %提取二維對角線方向細(xì)節(jié)系數(shù)ca1=appcoef2(c,s,39。)I=im2double(I)。LL頻帶保持了原始圖像的內(nèi)容信息，圖像的能量集中于此頻帶。壓縮后的圖像39。)I=im2double(I)。JPEG2000與傳統(tǒng)JPEG 最大的不同，在于放棄了JPEG所采用的以離散余弦轉(zhuǎn)換 (Discrete Cosine Transform)為主的區(qū)塊編碼方式，而采用以小波轉(zhuǎn)換( Wavelet transform)為主的多解析編碼方式。3．3常見壓縮方法香農(nóng)的率失真理論奠定了信源編碼的理論基礎(chǔ)?？v坐標(biāo)表示“模擬信號輸入幅度”，橫坐標(biāo)表示“編碼輸出”。即用實際值減去預(yù)測估計值得到差值信號，再將此差值信號量化、編碼和傳輸。選擇哪一類壓縮，要折衷考慮，盡管我們希望能夠無損壓縮，但是通常有損壓縮的壓縮比比無損壓縮的高。一個消息出現(xiàn)的可能性越小，其信息量就越多；而消息出現(xiàn)的可能性越大，其信息量就越少。(6)視覺冗余：某些圖像的失真是人眼不易覺察的。它將為網(wǎng)絡(luò)環(huán)境下的多媒體資源提供以下功能：內(nèi)容的創(chuàng)建、復(fù)制、分發(fā)、使用、表述，知識產(chǎn)權(quán)的管理與保護，內(nèi)容的標(biāo)識與描述，金融管理，用戶秘密，終端與網(wǎng)絡(luò)資源提取，事件報告等。對圖像壓縮而言，分形主要是利用自相似的特點，通過迭代函數(shù)系統(tǒng)來實現(xiàn)壓縮。MPEG7的應(yīng)用范圍很廣泛，既可應(yīng)用于存儲(在線或離線)，也可用于流式應(yīng)用(如廣播、將模型加入等)。(3)信息熵冗余：單位信息量大于其熵。信息論之父C．E．Shannon第一次用數(shù)學(xué)語言闡明了概率與信息冗余度的關(guān)系。據(jù)統(tǒng)計，圖像壓縮編碼方法已多達(dá)30一40種。由于預(yù)測誤差動態(tài)范圍大大縮小，因此只用3比特就可以了，這就減少了碼長，達(dá)到了壓縮的目的。當(dāng)差值P(f)為一個正的增量時用“1”碼來表示，當(dāng)差值P(r)為一個負(fù)的增量時用“0”碼來表示。為了盡可能避免出現(xiàn)斜率過載，就要加大量化階△，但這樣做又會加大粒狀噪聲；相反，如果要減小粒狀噪聲，就要減小量化階△，這又會使斜率過載更加嚴(yán)重。JPEG2000是國際化標(biāo)準(zhǔn)組織(ISO)和國際電子技術(shù)聯(lián)盟(IEC)聯(lián)合推出的新一代靜止圖像壓縮標(biāo)準(zhǔn)，自1997年開始起草，2000年12月國際標(biāo)準(zhǔn)(IS)正式發(fā)布，文檔代碼為ISO／IEC 15444—1。原始圖像大?。?9。,T)。圖像可以看做是二維矩陣。)。 %提取二維垂直方向細(xì)節(jié)系數(shù)cd1=detcoef2(39。ca139。其壓效效果顯而易見。39。,1)。mat39。 分析圖像壓縮算法應(yīng)當(dāng)從全面、系統(tǒng)觀點考慮，經(jīng)過靜止圖像的基于DCT和小波的編碼比較后，可知在圖像編碼中的主要因素是量化器和熵編碼器，而不是小波變換和 DCT的差別。從根本上說，小波壓縮機理正是體現(xiàn)在小波變換對圖像的多頻段分解恰與人類覺系統(tǒng)的多頻率通道特性相吻合，從而使我們能夠從人類視覺的多通道處理特性上對圖像進行相應(yīng)的壓縮處理。在此要感謝我的指導(dǎo)老師趙柯對我悉心的指導(dǎo)，感謝老師給我的幫助。s memory unit, can be coded up to 256 values. As opposed to the audio signal which is coded in the time domain, the image signal is coded in a two dimensional spatial domain. The raw image data is much more straightforward and easy to analyze than the temporal domain data of the audio signal. This is why we will be able to do lots of stuff and filters for images without transforming the source data, while this would have been totally impossible for audio signal. This first part deals with the simple effects and filters you can pute without transforming the source data, just by analyzing the raw image signal as it is.The standard dimensions, also called resolution, for a bitmap are about 500 rows by 500 columns. This is the resolution encountered in standard analogical television and standard puter applications. You can easily calculate the memory space a bitmap of this size will require. We have 500500 pixels, each coded on three bytes, this makes 750 Ko. It might not seem enormous pared to the size of hard drives, but if you must deal with an image in real time then processing things get tougher. Indeed rendering images fluidly demands a minimum of 30 images per second, the required bandwidth of 10 Mo/sec is enormous. We will see later that the limitation of data access and transfer in RAM has a crucial importance in image processing, and sometimes it happens to be much more important than limitation of CPU puting, which may seem quite different from what one can be used to in optimization issues. Notice that, with modern pression techniques such as JPEG 2000, the total size of the image can be easily reduced by 50 times without losing a lot of quality, but this is another topic.② Vector representation of colors As we have seen, in a bitmap, colors are coded on three bytes representing their deposition on the three primary colors. It sounds obvious to a mathematician to immediately interpret colors as vectors in a threedimension space where each axis stands for one of the primary colors. Therefore we will benefit of most of the geometric mathematical concepts to deal with our colors, such as norms, scalar product, projection, rotation or distance. This will be really interesting for some kind of filters we will see soon. Figure 1 illustrates this new interpretation: Figure 1(2) Immediate application to filters① Edge DetectionFrom what we have said before we can quantify the 39。s sharpness. Finally we will see later on that there is another way to make edge detection with matrix convolution.② Color extractionThe other immediate application of pixel parison is color of paring each pixel with its neighbors, we are going to pare it with a given color C1. This algorithm will try to detect all the objects in the image that are colored with C1. This was quite useful for robotics for example. It enables you to search on streaming images for a particular color. You can then make you robot go get a red ball for example. We will call the reference color, the one we are looking for in the image C0 = (R0,G0,B0). Once again, even if the square root can be easily removed it doesn39。在本文的工作期間趙老師嚴(yán)謹(jǐn)?shù)闹螌W(xué)態(tài)度、求實的治學(xué)作風(fēng)、對科學(xué)的執(zhí)著追求和大膽創(chuàng)新精神，令我深受感染并從中獲益匪淺：趙老師對我的嚴(yán)格要求和熱誠關(guān)懷使我無論在知識上還是實踐上都收獲頗多。經(jīng)過幾周的奮戰(zhàn)我的畢業(yè)設(shè)計終于完成了。如果要改變壓縮比，只需要調(diào)整程序中子矩陣的大小即可。)disp(39。 %顯示壓縮后的圖象title(39。h39。imshow(I)。,0)。 %保留小波分解第一層低頻信息ca1=wcodemat(ca1,440,39。)。HH頻帶保持了圖像在對角線方向上的高頻信息。)whos(39。P1*x*P239。d:\我的文檔\桌面\39。 JPEG2000與JPEG的區(qū)別JPEG是Joint Photographic Experts Group的縮寫?！鞅硎尽Ｔ隽空{(diào)制也稱△調(diào)制【9】(delta modulation，DM)，它是一種預(yù)測編碼技術(shù)，是PCM編碼的一種變形。預(yù)測編碼是一種簡單而且十分有效的數(shù)據(jù)壓縮方法，廣泛應(yīng)用于聲音，圖像等數(shù)據(jù)的壓縮。低于此極限的無失真編碼方法是不存在的?！　D像數(shù)據(jù)之所以能被壓縮，就是因為數(shù)據(jù)中存在著冗余。所以我們現(xiàn)今研究的重點是標(biāo)準(zhǔn)的研究。分形壓縮方法計算量比較大，時間開銷長，因此加快分形壓縮方法的速度是當(dāng)前研究的熱點之一。 視頻壓縮標(biāo)準(zhǔn)，從最初的H．261發(fā)展到現(xiàn)在盛行的MPEG4，一直在不斷發(fā)展，而1997年7月誕生了MPEG．7，其標(biāo)題為“多媒體內(nèi)容描述接口”，編號為ISO／IECl5938。為了去掉