Biosignal and Biomedical Image Processing MATLAB-Based Applications Muya phần 3 pot

... the original image and sharpness is reduced further by the cosine filter with its lowered bandwidth. (Original image from the MATLAB Image Processing Toolbox. Copyright 19 93 20 03, The Math Works, ... Figure 13. 7 which shows the square pattern of Figure 13. 5 sampled with one-half (left-hand image) and one-quarter (right-hand im- age) the number of parallel beams used in Figu...

Ngày tải lên: 23/07/2014, 19:20

... 4 .33 33 −0.6667 −0.1667 −0.6667 −0.1667 ͬ ; h gaussian = ͫ 0.01 13 0.0 838 0.01 13 0.0 838 0.61 93 0.0 838 0.01 13 0.0 838 0.01 13 ͬ The Laplacian filter is used to take the second derivative of an image: ∂ 2 /∂x. ... M]); % subplot(1 ,3, 1); imshow(I); %Display the images title(’Original Image ); subplot(1 ,3, 2); imshow(I_transform); title(’Transformed Image ); subplot(1 ,3, 3);...

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... inline(’x(2,2)—sum(x(1 :3, 1)) /3- sum(x(1 :3, 3)) /3 - x(1,2)—x (3, 2)’); I_diff = nlfilter(I, [3 3], F); % % Vertical boundary detection F1 = inline (’sum(x(1 :3, 2))—sum(x(1 :3, 1))’); I_vertical = nlfilter(I, [3 2], ... nlfilter(I, [3 3], ‘mean2’); This command will slide a 3 by 3 moving average across the image pro- ducing a lowpass filtered version of the original image (an...

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... by con- volving the reference signal with a lowpass filter consisting of 3 equal weights; i.e: b = [ 0 .33 3 0 .33 3 0 .33 3]. For this more realistic scenario, note the degradation in performance ... *sin(w*12) ؉ .1*randn(1,N); % Double sin, a sawtooth s2 = sawtooth(w*5,.5)؉ .1*randn(1,N); % and a periodic % function s3 = pulstran((0:999),(0:5)’*180,kaiser(100 ,3) ) ؉ .07*randn(1,N); % %...

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... Example 7 .3. In some analysis applications only the subband signals are of interest and reconstruction is not needed, but in many wavelet applications, some operation is performed on the subband signals, ... adjusted to approxim ate a bandpass filter with a small bandwidth and a p eak a t 10 H z. TLFeBOOK 8 Advanced Signal Processing Techniques: Optimal and Adaptive Filters OPTIMA...

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... Choi-Williams and Rihaczek-Margenau dis- tributions for both a double sinusoid and chirp stimulus. Plot the Rihaczek- Margenau determining function* and the results using 3- D type plots. % Example 6.5 and ... magnitude figure; mesh(t,f,B); % Plot Spectrogram as 3- D mesh view(160,40); % Change 3- D plot view axis([0 2 0 100 0 20]); % Example of axis and xlabel(’Time (sec)’); % l...

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... Example 4.5 and Figure 4. 13 % Bandstop filter with a passband gain of 1 between 0 and 100, % a stopband gain of -40 db between 30 0 and 400 Hz, % and an upper passband gain of 1 between 500 and fs/2 ... Design a bandstop filter having the following characteris- tics: a passband gain of 1 (0 db) between 0 and 100, a stopband gain of −40 db between 30 0 and 400 Hz, and an up...

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... and can be found in the help file for pwelch . Example 3. 2 Apply Welch’s method to the sine plus noise data used in Example 3. 1. Use 124-point data segments and a 50% overlap. % Example 3. 2 and ... construct an impulse func- tion and determine the output using the MATLAB filter routine. % Example 4.1 and Figures 4.2 and 4 .3 % Plot the frequency characteristics and impuls...

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... Generate bandlimited noise and compute and plot the auto- correlation function for two different bandwidths. % Example 2.2 and Figure 2.8 % Generate colored noise having two different bandwidths % and ... is, construct a filter function consisting of 3 equal co ef ficie nts of 1 /3: (h(n) = [1 /3 1 /3 1 /3] ) . Then convolve this weighting function with the random array using con...

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... Transformations 32 6 Image Registration 33 1 Unaided Image Registration 33 3 Interactive Image Registration 33 7 Problems 33 9 12 Image Segmentation 34 3 Pixel-Based Methods 34 3 Threshold Level Adjustment 34 4 MATLAB ... Concepts 31 Noise 31 Ensemble Averaging 34 MATLAB Implementation 35 Data Functions and Transforms 37 Convolution, Correlation, and Covariance 4...

Ngày tải lên: 23/07/2014, 19:20