%%?Deblurring?Images?Using?the?Blind?Deconvolution?Algorithm?
%%盲反卷積算法復原圖像
%?The?Blind?Deconvolution?Algorithm?can?be?used?effectively?when?no
%?information?about?the?distortion?（blurring?and?noise）?is?known.?The
%?algorithm?restores?the?image?and?the?point-spread?function?（PSF）
%?simultaneously.?The?accelerated?damped?Richardson-Lucy?algorithm?is?used
%?in?each?iteration.?Additional?optical?system?（e.g.?camera）
%?characteristics?can?be?used?as?input?parameters?that?could?help?to
%?improve?the?quality?of?the?image?restoration.?PSF?constraints?can?be
%?passed?in?through?a?user-specified?function
%在不知道圖像失真信息（模糊和噪聲）信息情況下，盲反卷積算法可以有效地加以利用。該算法
%對圖像和點擴展函數（PSF）的同時進行復原。每次迭代都使用加速收斂Richardson-Lucy?
%算法。額外的光學系統（如照相機）的特性可作為輸入參數，幫助改善圖像復原質量?？梢酝?br/>%過用戶指定的函數對PSF進行限制
%?Copyright?2004-2005?The?MathWorks?Inc.
?
%%?Step?1:?Read?Image
%%第一步：讀取圖像
%?The?example?reads?in?an?intensity?image.?The?|deconvblind|?function?can
%?handle?arrays?of?any?dimension.
%該示例讀取一個灰度圖像。|?deconvblind?|函數可以處理任何維數組。
I?=?imread（‘cameraman.tif‘）;
figure;imshow（I）;title（‘Original?Image‘）;
text（size（I2）size（I1）+15?...
????‘Image?courtesy?of?Massachusetts?Institute?of?Technology‘?...
‘FontSize‘7‘HorizontalAlignment‘‘right‘）;??
???

?
%%?Step?2:?Simulate?a?Blur
%%第二步：模擬一個模糊
%?Simulate?a?real-life?image?that?could?be?blurred?（e.g.?due?to?camera
%?motion?or?lack?of?focus）.?The?example?simulates?the?blur?by?convolving?a
%?Gaussian?filter?with?the?true?image?（using?|imfilter|）.?The?Gaussian?filter
%?then?represents?a?point-spread?function?|PSF|.
?%模擬一個現實中存在的模糊圖像（例如，由于相機抖動或對焦不足）。這個例子通過對真實
%圖像進行高斯濾波器模擬圖像模糊（使用|imfilter|）。高斯濾波器是一個點擴展函數，
%|PSF|。
PSF=fspecial（‘gaussian‘710）;
Blurred=imfilter（IPSF‘symmetric‘‘conv‘）;??%對圖像I進行濾波處理；
figure;imshow（Blurred）;title（‘Blurred?Image‘）;??

???

?
%%?Step?3:?Restore?the?Blurred?Image?Using?PSFs?of?Various?Sizes
%%第三步：使用不同的點擴展函數復原模糊圖像
%?To?illustrate?the?importance?of?knowing?the?size?of?the?true?PSF?this
%?example?performs?three?restorations.?Each?time?the?PSF?reconstruction
%?starts?from?a?uniform?array--an?array?of?ones.
%為了說明知道真實PSF的大小的重要性，這個例子執行三個修復。PSF函數重建每次都是從統一
%的全一數組開始。
%%
%?The?first?restoration?|J1|?and?|P1|?uses?an?undersized?array?|UNDERPSF|?for
%?an?initial?guess?of?the?PSF.?The?size?of?the?UNDERPSF?array?is?4?pixels
%?shorter?in?each?dimension?than?the?true?PSF.?
%第一次復原，|J1|和|P1|，使用一個較小數組，|?UNDERPSF?|，來對PSF的初步猜測。該
%UNDERPSF數組每維比真實PSF少4個元素。
UNDERPSF?=?ones（size（PSF）-4）;
[J1?P1]?=?deconvblind（BlurredUNDERPSF）;
figure;imshow（J1）;title（‘Deblurring?with?Undersized?PSF‘）;?

???

%%
%?The?second?restoration?|J2|?and?|P2|?uses?an?array?of?ones?|OVERPSF|?for?an
%?initial?PSF?that?is?4?pixels?longer?in?each?dimension?than?the?true?PSF.
%第二次復原，|J2|和|P2|，使用一個元素全為1的數組，|?OVERPSF|，初始PSF每維比真
%實PSF多4個元素。
OVERPSF?=?padarray（UNDERPSF[4?4]‘replicate‘‘both‘）;
[J2?P2]?=?deconvblind（BlurredOVERPSF）;
figure;imshow（J2）;title（‘Deblurring?with?Oversized?PSF‘）;??
???

?
%%
%?The?third?restoration?|J3|?and?|P3|?uses?an?array?of?ones?|INITPSF|?for?an
%?