%%?Deblurring?Images?Using?the?Blind?Deconvolution?Algorithm???
%%盲反卷積算法復(fù)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(duì)圖像和點(diǎn)擴(kuò)展函數(shù)（PSF）的同時(shí)進(jìn)行復(fù)原。每次迭代都使用加速收斂Richardson-Lucy???
%算法。額外的光學(xué)系統(tǒng)（如照相機(jī)）的特性可作為輸入?yún)?shù)，幫助改善圖像復(fù)原質(zhì)量?？梢酝??
%過(guò)用戶指定的函數(shù)對(duì)PSF進(jìn)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(gè)灰度圖像。|?deconvblind?|函數(shù)可以處理任何維數(shù)組。??
I?=?imread（‘flame_gray_1.bmp‘）;??
figure;imshow（I）;title（‘Original?Image‘）;??%figure1
%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(gè)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(gè)現(xiàn)實(shí)中存在的模糊圖像（例如，由于相機(jī)抖動(dòng)或?qū)共蛔悖?。這個(gè)例子通過(guò)對(duì)真實(shí)??
%圖像進(jìn)行-高斯濾波器-模擬圖像模糊（使用|imfilter|）。高斯濾波器是一個(gè)點(diǎn)擴(kuò)展函數(shù)，??
%|PSF|。??
%h=fspecial（‘高斯’，hsize，sigma），返回一個(gè)旋轉(zhuǎn)對(duì)稱的高斯低通濾波器，大小為hsize，標(biāo)準(zhǔn)偏差σ（正）默認(rèn)0.5。
%不推薦，使用imgaussfilt或imgaussfilt3代替。
PSF=fspecial（‘gaussian‘710）;???%創(chuàng)建一個(gè)預(yù)先定義的二維過(guò)濾器psf
Blurred=imfilter（IPSF‘symmetric‘‘conv‘）;??%對(duì)圖像I進(jìn)行濾波處理；??
figure;imshow（Blurred）;title（‘Blurred?Image‘）;????%figure2
??
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??
???
%%?Step?3:?Restore?the?Blurred?Image?Using?PSFs?of?Various?Sizes??
%%第三步：使用不同的點(diǎn)擴(kuò)展函數(shù)復(fù)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(shuō)明知道真實(shí)PSF的大小的重要性，這個(gè)例子執(zhí)行三個(gè)修復(fù)。PSF函數(shù)重建每次都是從統(tǒng)一??
%的全一數(shù)組開(kāi)始。??
%%??第一次較小數(shù)組復(fù)原
%?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(fù)原，|J1|和|P1|，使用一個(gè)較小數(shù)組，|?UNDERPSF?|，來(lái)對(duì)PSF的初步猜測(cè)。該??
%UNDERPSF數(shù)組每維比真實(shí)PSF少4個(gè)元素。??
UNDERPSF?=?ones（size（PSF）-4）;??
[J1?P1]?=?deconvblind（BlurredUNDERPSF）;??
figure;imshow（J1）;title（‘Deblurring?with?Undersized?PSF‘）;???%figure3
??
?????
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%%??第二次較大數(shù)組復(fù)原
%?The?second?restoration?|J2|?and?|P2|?uses?an?array?of?ones?|OVERPSF|?for?an??
%?initial?P