1 簡介

Harris 角點(diǎn)檢測算法是由?C.Harris 和 J.Stephens 在 1988 年提出，此算法的原理是建立在?Moravec 算法的基礎(chǔ)上進(jìn)行大幅改進(jìn)的，相比之前的算法更具明顯的優(yōu)勢。Moravec如上文中的介紹說明，相比?Harris?檢測算法而言，

Moravec 檢測算法僅僅只是是在水平、垂直、對角線和反對角線四個方向上對灰度變化的信息進(jìn)行處理，而 Harris 檢測算法受到數(shù)學(xué)理論泰勒（Taylor

）級數(shù)的啟發(fā)，以此展開思路，已不只是限定于四個方向，而是計(jì)算窗口內(nèi)沿任意方向的灰度變化情況，最終利用數(shù)學(xué)解析式進(jìn)一步確定所需特征點(diǎn)。并且算法引入高斯平滑算子，更加優(yōu)化了算法自身的魯棒性。不僅如此，Harris?

檢測算法還受到信號處理中自相關(guān)函數(shù)的啟迪，從而使用了自相關(guān)函數(shù)相關(guān)聯(lián)的 M?矩陣。

該算法中 M?矩陣的特征值即自相關(guān)函數(shù)的一階求導(dǎo)函數(shù)，判斷該點(diǎn)是否為特征點(diǎn)即看此處像素點(diǎn)的曲率值是否夠高。

2 部分代碼

function [imgout]=warpTheImage(H,img1,img2)tform = maketform('projective',H');img21 = imtransform(img2,tform); % reproject img2% [M1 N1 dim] = size(img1);[M2 N2 dimk1] = size(img2);% do the mosaicpt = zeros(3,4);pt(:,1) = H*[1;1;1];pt(:,2) = H*[N2;1;1];pt(:,3) = H*[N2;M2;1];pt(:,4) = H*[1;M2;1];x2 = pt(1,:)./pt(3,:);y2 = pt(2,:)./pt(3,:);up = round(min(y2));Yoffset = 0;if up <= 0 ?Yoffset = -up+1; ?up = 1;endleft = round(min(x2));Xoffset = 0;if left<=0 ?Xoffset = -left+1; ?left = 1;end[M3 N3 dimk2] = size(img21);rowBegin=max(up,Yoffset+1); %overlap AreacolumnBegin=max(left,Xoffset+1);rowEnd=min(up+M3-1,Yoffset+M1);columnEnd=min(left+N3-1,Xoffset+N1);imgout(up:up+M3-1,left:left+N3-1,:) = img21;overlapAreaP2=imgout(rowBegin:rowEnd,columnBegin:columnEnd,:);%pixel values of overlap area from P2% img1 is above img21imgout(Yoffset+1:Yoffset+M1,Xoffset+1:Xoffset+N1,:) = img1;overlapAreaP1=imgout(rowBegin:rowEnd,columnBegin:columnEnd,:); overlapArea=imgout(rowBegin:rowEnd,columnBegin:columnEnd); [overRowLength,overColumnLength]=size(overlapArea);%overlap Row and Column length distFromBound1OneLine=(overColumnLength-1:-1:0);%this is just one line distFromBound1=repmat(distFromBound1OneLine,overRowLength,1); ?%Replicate and tile it to the size of the overlapArea. Because the same column has the same distance to the boundary distFromBound2OneLine=(0:overColumnLength-1); distFromBound2=repmat(distFromBound2OneLine,overRowLength,1);%this the dist from boundary 2 % blending% ?blendingImg(:,:,:)=(overlapAreaP2(:,:,:).*distFromBound2+overlapAreaP1(:,:,:).*distFromBound1)/(overColumnLength-1);% imshow(blending)overlapAreaP2=double(overlapAreaP2);overlapAreaP1=double(overlapAreaP1);blendingImg=zeros(overRowLength,overColumnLength,3);for i=1:3blendingImg(:,:,i)=(overlapAreaP2(:,:,i).*distFromBound2+overlapAreaP1(:,:,i).*distFromBound1)/(overColumnLength-1);endblendingImg=uint8(blendingImg);% imshow(blendingImg);title('after blending'); imgout(rowBegin:rowEnd,columnBegin:columnEnd,:)=blendingImg;end

3 仿真結(jié)果

4 參考文獻(xiàn)

[1]賈瑩. 基于Harris角點(diǎn)檢測算法的圖像拼接技術(shù)研究[D]. 吉林大學(xué).

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