图像中Mutual information的计算公式一般如下： 这之中涉及到两个方面的内容，一个是联合的直方图，一个是各自的直方图。下面是参考代码：
function res = computeMI(img1,img2,bins) %Compute mutual information %Quantify images img1 = im2double(uint16(img1)); img2 = im2double(uint16(img2)); img1 = floor(img1*bins);%Quantify img2 = floor(img2*bins); %参考： %https://www.mathworks.com/matlabcentral/fileexchange/6978-image-registration-2d-using-mutual-information-optimization-toolbox-needed [rows,cols] = size(img1); h = hist2d ([img1(:),img2(:)], 0:1:100, 0:1:100); [r,c] = size(h); b= h./(r*c); % normalized joint histogram y_marg=sum(b); %sum of the rows of normalized joint histogram x_marg=sum(b');%sum of columns of normalized joint histogran Hy=0; for i=1:c % col if( y_marg(i)==0 ) %do nothing else Hy = Hy + -(y_marg(i)*(log2(y_marg(i)))); %marginal entropy for image 1 end end Hx=0; for i=1:r %rows if( x_marg(i)==0 ) %do nothing else Hx = Hx + -(x_marg(i)*(log2(x_marg(i)))); %marginal entropy for image 2 end end h_xy = -sum(sum(b.*(log2(b+(b==0))))); % joint entropy res=-(Hx+Hy-h_xy);% Mutual information %x end % https://www.mathworks.com/matlabcentral/fileexchange/1487-2d-histogram-matrix function mHist = hist2d (mX, vYEdge, vXEdge) nCol = size(mX, 2); if nCol < 2 error ('mX has less than two columns') end nRow = length (vYEdge)-1; nCol = length (vXEdge)-1; vRow = mX(:,1); vCol = mX(:,2); mHist = zeros(nRow,nCol); for iRow = 1:nRow rRowLB = vYEdge(iRow); rRowUB = vYEdge(iRow+1); vColFound = vCol((vRow > rRowLB) & (vRow <= rRowUB)); if (~isempty(vColFound)) vFound = histc (vColFound, vXEdge); nFound = (length(vFound)-1); if (nFound ~= nCol) disp([nFound nCol]) error ('hist2d error: Size Error') end [nRowFound, nColFound] = size (vFound); nRowFound = nRowFound - 1; nColFound = nColFound - 1; if nRowFound == nCol mHist(iRow, :)= vFound(1:nFound)'; elseif nColFound == nCol mHist(iRow, :)= vFound(1:nFound); else error ('hist2d error: Size Error') end end end end链接中也给出了引用地址。
