How to inport the data. Part 1: How to use image data

Transcription

1 How to inport the data Part 1: How to use image data

2 Example 1 >> kou=imread( kou.jpg','jpg'); Or File inport date kou.jpg kou(:,:,1) : Red kou(:,:,2) : Green kou(:,:,3) : Blue >> whos kou Name Size Bytes Class kou 213x255x uint8 array Grand total is elements using bytes >> image(kou) image(kou(:,:,1)) : Red image(kou(:,:,2)) : Green image(kou(:,:,3)) : Blue

3 Command : imread IMREAD Read image from graphics file. Agif=imread('barfy1.gif','gif'); Ajpg=imread('m_pic2.jpg','jpg'); A = IMREAD(FILENAME,FMT) reads a grayscale or color image from the file specified by the string FILENAME, where the string FMT specifies the format of the file. IMREAD returns the image data in the array A. If the file contains a grayscale image, A is a two-dimensional (Mby-N) array. If the file contains a color image, A is a three-dimensional (M-by-N-by-3) array.

4 Command : imwrite IMWRITE Write image to graphics file. imwrite(kou, kou2.jpg, 'jpeg') ; IMWRITE(A,FILENAME,FMT) writes the image A to FILENAME. FILENAME is a string that specifies the name of the output file, and FMT is a string the specifies the format of the file. kou can be either a grayscale image (M-by-N) or a truecolor image (M-by-N-by-3).

5 Example 2 filename = kou.jpg'; A = imread(filename,'jpeg') ; % size(a) %imshow(a); image(a); image(a(:,:,1)); B1 = double(a(:,:,1)); % image(a(:,:,2)); B2 = double(a(:,:,2)); % image(a(:,:,3)); B3 = double(a(:,:,3)); C= FFT2(B1); % C = fftshift(c); D=log10(abs(C)+1); dmax = max(max(d)); E = uint8(d/dmax * 255);% figure; %imshow(e);%... image(e); % filename1 = kou2.jpg'; imwrite(e, filename1, 'jpeg') ;

6 Sample 3 Agif=imread('barfy1.gif','gif'); figure(1),imshow(agif) figure(2),image(agif) figure(3),colormap(gray);image(agif); figure(4),colormap(hsv);image(agif); figure(5),colormap(hot);image(agif); figure(6),colormap(gray(2^8));image(agif);

7 Sample 4 % averaging clear Agif=imread('barfy1.gif','gif'); Adbl=double(Agif); rca=size(adbl); h=[ ]/4; for i=1:rca(2) Bdbl(:,i)=conv(h,Adbl(:,i)); end colormap(gray);image(bdbl); rcb=size(bdbl); for i=1:rcb(1) Cdbl(i,:)=conv(h,Bdbl(i,:)); end colormap(gray);image(cdbl); rcc=size(cdbl); h=[ ]; for i=1:rcc(2) Edbl(:,i)=conv(h,Cdbl(:,i)); end colormap(gray);image(edbl); %Fdbl=Adbl*100; dmax=max(max(fdbl)); Gdbl=uint8(Fdbl/dmax*255); colormap(gray);image(gdbl);

8 Sample 5 Image Proccessing Toolbox

9 Part 2 : How to use wave data

10 Sample 1 CD-Rom Kita2004 samples2 acoust listenwave.m [y, fs, bits] = wavread('clicks.wav'); sound(y,fs);

11 Sample 2 CD-Rom Kita2004 samples2 acoust File name acoust_synthesis.m % Create 440Hz % t=0:1/44100:1; y1=0.9*sin(2*pi*440*t); wavwrite(y1,44100,16,'testsindat1.wav'); % y2=0.4*sin(2*pi*440*t) + 0.3*sin(2*pi*880*t) *sin(2*pi*1320*t); wavwrite(y2,44100,16,'testsindat2.wav'); % FM ongen y3=0.9*sin(2*pi*220*t + sin(2*pi*10*t)); wavwrite(y2,44100,16,'testsindat3.wav'); %Amplitude modulation A=linspace(0.99,0,length(t)); y4=a.*sin(2*pi*440*t); wavwrite(y4,44100,16,'testsindat4.wav'); % frequency modulation f=linspace(440,880,length(t)); y5=0.9*sin(2*pi*f.*t); wavwrite(y5,44100,16,'testsindat5.wav'); % [y1d, fs1, bits1] = wavread('testsindat1.wav'); sound(y1d,fs1); disp('paused... hit any key'); [y2d, fs2, bits2] = wavread('testsindat2.wav'); sound(y2d,fs2); disp('paused... hit any key'); [y3d, fs3, bits3] = wavread('testsindat3.wav'); sound(y3d,fs3); disp('paused... hit any key'); [y4d, fs4, bits4] = wavread('testsindat4.wav'); sound(y4d,fs4); disp('paused... hit any key'); [y5d, fs5, bits5] = wavread('testsindat5.wav'); sound(y5d,fs5);

12 Sample 3 CD-Rom Kita2004 samples2 acoust stanford_clipping.m [y, fs, bits] = wavread('soundffile.wav'); %Even after severe peak clipping, intelligibility remains high y = y/max(abs(y)); sound(y,fs); disp('paused... hit any key'); N = length(y); cliplevel = 0.02; for i = 1:N, if abs(y(i)) > cliplevel y(i) = sign(y(i))*cliplevel; end end sound(y,fs);

13 Sample 4 CD-Rom Kita2003 samples2 acoust [y, fs, bits] = wavread('guitar.wav'); % Noise masking can reduce intelligibility of individual words by about 50% % when the average intensities of the speech and noise are about equal. % However, linguistic and semantic cues still allow intelligibility of sentences y = y/max(abs(y)); sound(y,fs); disp('paused... hit any key'); noisescale = 0.8; n = rand(size(y)); n = (n-0.5)*2*noisescale; y = (y + n)/2; sound(y,fs); stanford_noisespeech.m

14 Part 3 : How to use the excel data

15 How to inport data from Excel file Method 1: 1. Create excel data file 2. Use inport data in MATLAB File menu

16 How to inport data from Excel file Method 2: 1. Create the function M-file Filename : xel2matdde.m function A = xcel2matdde(row,col) channel = ddeinit('excel','sheet1'); if channel == 0, error('error initiating conversation'); end Asize(2) = col; Asize(1) = row; worksheet=sprintf('r1c1:r%dc%d',asize); A = ddereq(channel,worksheet); ddeterm(channel); 2. Run Excel and open the excel file 3. Call the function M-file in Command window EDU>> X = xcel2matdde(3,2)

17 How to export data to Excel file Method 1: 1. Save data as the ASCII file EDU>>save data3.dat X /ascii 2. Run excel and open the ASCII file

18 How to inport data from Excel file Method 2: 1. Create the function M-file Filename : mat2xceldde.m function void = mat2xceldde(a) channel = ddeinit('excel','sheet1'); if channel == 0, error('error initiating conversation'); end Asize = size(a); worksheet=sprintf('r1c1:r%dc%d',asize); rc = ddepoke(channel,worksheet,a); if rc == 0, error('error poking data'); end ddeterm(channel); 2. Run Excel and open the new excel file 3. Call the function M-file in Command window EDU>> mat2xceldde([1 0 0;0 1 0;0 0 1])