《信息論與編碼》實驗報告

1、精品文檔?信息論與編碼?實驗報告QQ417860489一、實驗?zāi)康?、理解信源編碼的根本原理；2、熟練掌握Huffman編碼的方法；3、理解無失真信源編碼和限失真編碼方法在實際圖像信源編碼應(yīng)用中的差異。二、實驗設(shè)備與軟件 1、PC計算機(jī)系統(tǒng) 2、VC+6.0語言編程環(huán)境 3、基于VC+6.0的圖像處理實驗根本程序框架imageprocessing4、常用圖像瀏覽編輯軟件Acdsee和數(shù)據(jù)壓縮軟件winrar。5、實驗所需要的bmp格式圖像灰度圖象假設(shè)干幅。三、實驗內(nèi)容與步驟 1、針對“圖像1.bmp、“圖像2.bmp和“圖像3.bmp進(jìn)行灰度頻率統(tǒng)計即計算圖像灰度直方圖，在此根底上添加函數(shù)代碼

2、構(gòu)造Huffman碼表，針對圖像數(shù)據(jù)進(jìn)行Huffman編碼，觀察和分析不同圖像信源的編碼效率和壓縮比。1各個圖像的灰度頻率統(tǒng)計如下2對圖像1進(jìn)行Huffman編碼，得到碼表如下像素值概率分布Huffman編碼未差分像素值概率分布Huffman編碼未差分像素值概率分布Huffman編碼未差分00.0118360001101000.0000002000.00000010.0000001010.01003311001012010.00000020.0000001020.0000002020.01598310010130.0000001030.0000002030.00000040.021309111

3、1011040.0000002040.00000050.0000001050.0194301110002050.00000060.0000001060.0000002060.01524101111070.0000001070.0000002070.00000080.022653000011080.0000002080.00000090.0000001090.0133950100112090.000000100.0000001100.0000002100.012887010001110.0000001110.0000002110.000000120.0037240110011011120.000

4、0002120.000000130.0000001130.0140170101112130.000000140.0000001140.0000002140.000000150.0000001150.0000002150.017783101101160.022806000101160.0000002160.000000170.0000001170.0164751001112170.000000180.0000001180.0000002180.000000190.0000001190.0000002190.012412001100200.004404011001111200.0000002200

5、.000000210.0000001210.0164941010002210.000000220.0000001220.0000002220.000000230.0000001230.0000002230.020212111001240.0189911101011240.0000002240.000000250.0000001250.0181411100002250.000000260.0000001260.0000002260.000000270.0000001270.0000002270.017126101010280.0211981110111280.0000002280.0000002

6、90.0000001290.0000002290.000000300.0000001300.0139580101102300.000000310.0000001310.0000002310.015326011111320.01028311111001320.0000002320.000000330.0000001330.0000002330.000000340.0000001340.0125940011102340.000000350.0000001350.0000002350.012412001101360.0212701111001360.0000002360.000000370.0000

7、001370.0000002370.000000380.0000001380.0135550101012380.000000390.0000001390.0000002390.015895100011400.0126760011111400.0000002400.000000410.0000001410.0000002410.000000420.0000001420.0191441101112420.000000430.0000001430.0000002430.02472700100440.0000001440.0000002440.000000450.0155961000011450.00

8、00002450.000000460.0000001460.0155921000002460.000000470.0000001470.0000002470.00587211111011480.0000001480.0000002480.000000490.022113000001490.0000002490.000000500.0000001500.0132850100102500.000000510.0000001510.0000002510.014531011010520.0000001520.0000002520.000000530.005234111110101530.0000002

9、530.000000540.0000001540.0186201100112540.000000550.0000001550.0000002550.018734110100560.0000001560.000000570.0190691101101570.000000580.0000001580.016113100110590.0000001590.000000600.0000001600.000000610.0180311011111610.000000620.0000001620.014222011000630.0000001630.000000640.0000001640.0000006

10、50.0118680001111650.000000660.0000001660.017660101100670.0000001670.000000680.0000001680.000000690.024749001011690.000000700.0000001700.018018101110710.0000001710.000000720.0000001720.000000730.00624701100101730.000000740.0000001740.016758101001750.0000001750.000000760.0000001760.000000770.014762011

11、0111770.000000780.0000001780.012868010000790.0000001790.000000800.0000001800.000000810.0157061000101810.000000820.0000001820.0084701100100830.0000001830.000000840.0000001840.000000850.0206801110101850.000000860.0000001860.017607101011870.0000001870.000000880.0000001880.000000890.0159051001001890.000

12、000900.0000001900.021755111111910.0000001910.000000920.0000001920.000000930.0149480111011930.000000940.0000001940.013438010100950.0000001950.000000960.0000001960.000000970.0183431100011970.000000980.0000001980.014837011100990.0000001990.000000由表中的規(guī)律可以看出，沒4個像素點中只有一個的概率不為0，說明此圖進(jìn)行過量化，實際用到的像素點只有64個。3各幅圖

13、像信源的編碼效率和壓縮比編碼效率:平均每個碼符號的最大信息量為logm=log2=1比特/碼符號，平均每個信源符號的信息量為H(U)比特/信源符號，平均碼長為K碼符號/信源符號，那么=H(U)K*logm=H(U)K。壓縮比L：在進(jìn)行Huffman編碼前，每個像素由8個比特位表示，編碼后平均每個灰度值的碼長為K，所以L=8/K。編碼效率和壓縮比方下表： 質(zhì)量因子圖像信源熵比特/符號平均碼長碼符號/信源符號編碼效率壓縮比圖像15.92855.96020.99471.3422圖像24.40974.44360.99241.8003圖像36.70866.73360.99631.18814用到的主要代碼

14、如下：void CImageProcessingDoc:OnImageHuffmancode() int m_Width, m_Height, m_SaveWidth;int i,j;/循環(huán)變量double hist256 = 0; /概率分布m_Width = m_pDibInit->GetWidth();m_Height = m_pDibInit->GetHeight();m_SaveWidth = m_pDibInit->GetSaveWidth();hx = 0.0; /信源熵km = 0.0; /平均碼長ys = 0.0; /壓縮比/計算概率分布for(j=0;j&

15、lt;m_Height;j+)for(i=0;i<m_Width;i+)histm_pDibInit->m_pDibBitsj*m_SaveWidth+i=histm_pDibInit->m_pDibBitsj*m_SaveWidth + i+1.0/double(m_Width*m_Height);/輸出概率統(tǒng)計histFILE*fphist; FILE*fpcode; fphist=fopen("hist.txt","w"); fpcode=fopen("code.txt","w"); for

16、(i=0;i<256;i+) fprintf(fphist,"%fn",histi);/計算Huffman編碼Huffm huffm(256); /實例化Huffman類huffm.Huffman(hist); /huffm.HuffmanCode(); /進(jìn)行Huffman編碼codetype co; /定義code結(jié)構(gòu)體cofor(i=0;i<256;i+)if(histi=0)continue; hx = hx - histi*log(histi)/log(2);/信源熵 co = huffm.codei; /讀取Huffman編碼 km = km + h

17、isti*(256-co.start); /計算平均碼長/輸出編碼code for(i=0;i<256;i+)co = huffm.codei; for(j=co.start;j<256;j+)fprintf(fpcode,"%d",(int)(co.bitsj - '0');fprintf(fpcode,"n");ys = 8/km; /壓縮比 xl = hx/(km); /編碼效率 test = 1; /顯示判據(jù) UpdateAllViews(NULL);2、利用圖像處理軟件Acdsee將“圖像1.bmp、“圖像2.bmp

18、和“圖像3.bmp轉(zhuǎn)換為質(zhì)量因子為10、50、90的JPG格式圖像共生成9幅JPG圖像，比擬圖像格式轉(zhuǎn)換前后數(shù)據(jù)量的差異，比擬不同品質(zhì)因素對圖像質(zhì)量的影響； 不同質(zhì)量的圖像數(shù)據(jù)量如下表： 原始105090圖像1302 KB35 KB53 KB142 KB圖像2302 KB32 KB49 KB114 KB圖像3302 KB52 KB78 KB175 KB 由表可見，三幅圖原始大小相同，隨著質(zhì)量因子的減小，數(shù)據(jù)量也均在減小，但各幅圖減小壓縮比并不相同。3、數(shù)據(jù)壓縮軟件winrar將“圖像1.bmp、“圖像2.bmp和“圖像3.bmp分別生成壓縮包文件，觀察和分析壓縮前后數(shù)據(jù)量的差異；壓縮前后數(shù)據(jù)量

19、如下表： 圖像1圖像2圖像3壓縮前302 KB302 KB302 KB壓縮后151 KB124 KB218 KB4、針對任意一幅圖像，比擬原始BMP圖像數(shù)據(jù)量、Huffman編碼后的數(shù)據(jù)量不含碼表、品質(zhì)因數(shù)分別為10、50、90時的JPG文件數(shù)據(jù)量和rar壓縮包的數(shù)據(jù)量，分析不同編碼方案下列圖像數(shù)據(jù)量變化的原因。以圖像1為例，其原始BMP圖像數(shù)據(jù)量、Huffman編碼后的數(shù)據(jù)量不含碼表、品質(zhì)因數(shù)分別為10、50、90時的JPG文件數(shù)據(jù)量和rar壓縮包的數(shù)據(jù)量分別如下表所示：原始BMPHuffman編碼JPGrar壓縮包105090302 KB224 KB35 KB53 KB142 KB151 KB由表可知，進(jìn)行編碼后，數(shù)據(jù)量較原始BMP文件均有減小，其中，Huffman編碼和rar壓縮包的數(shù)據(jù)量比擬大，這是由于其編碼過程中只進(jìn)行了去除冗余，并沒有進(jìn)行量化，屬于無失真編碼；而JPG格式的文件數(shù)據(jù)量隨著其品質(zhì)因數(shù)不同差異很大，這是由于在編碼過程中進(jìn)行了量化，從而產(chǎn)生了失真，品質(zhì)因數(shù)越大，圖片質(zhì)量越好，失真越小，文件的數(shù)據(jù)量也越大。5、先對圖像進(jìn)行差分再進(jìn)行Huffman編碼。 信源熵比特/符號平均碼長碼符號/信源符號編碼效率壓縮比圖像14.05014.07940.99281.9610圖像24.195