导致黑色图像的分水岭算法中的负值

Question

我正在使用分水岭算法尝试和分割触摸核。典型的图像可能看起来像： 或本：

我想使用此代码应用分水岭算法：

show(RGB_img) 


%Convert to grayscale image 
I = rgb2gray(RGB_img); 

%Take structuring element of a disk of size 10, for the morphological transformations 
%Attempt to subtract the background from the image: top hat is the 
%subtraction of the open image from the original 


%Morphological transformation to subtract background noise from the image 
%Tophat is the subtraction of an opened image from the original. Remove all 
%images smaller than the structuring element of 10 
I1 = imtophat(I, strel('disk', 10)); 

%Increases contrast 
I2 = imadjust(I1); 
%show(I2,'contrast') 
%Assume we have background and foreground and assess thresh as such 
level = graythresh(I2); 
%Convert to binary image based on graythreshold 
BW = im2bw(I2,level); 
show(BW,'C'); 



BW = bwareaopen(BW,8); 
show(BW,'C2'); 

BW = bwdist(BW) <= 1; 
show(BW,'joined'); 
%Complement because we want image to be black and background white 
C = ~BW; 
%Use distance tranform to find nearest nonzero values from every pixel 
D = -bwdist(C); 

%Assign Minus infinity values to the values of C inside of the D image 
% Modify the image so that the background pixels and the extended maxima 
% pixels are forced to be the only local minima in the image (So you could 
% hypothetically fill in water on the image 

D(C) = -Inf; 

%Gets 0 for all watershed lines and integers for each object (basins) 
L = watershed(D); 
show(L,'L'); 

%Takes the labels and converts to an RGB (Using hot colormap) 
fin = label2rgb(L,'hot','w'); 

% show(fin,'fin'); 
im = I; 

%Superimpose ridgelines,L has all of them as 0 -> so mark these as 0(black) 
im(L==0)=0; 

clean_img = L; 
show(clean_img) 

C = ~BW;之后整个图像变暗。我相信这是因为图像像素都是-inf或一些较小的负数。这是有解决方法，如果是这样的话，我可以在我的代码中更改什么以获得此算法的工作？我已经试验了一大堆，我不知道发生了什么。任何帮助将是伟大的！

Answer 1

问题出在您的show命令。正如你在评论中所说的那样，它使用了imshow。如果你直接尝试imshow，你会看到你也会得到一个黑色的图像。但是，如果您将其称为适当限制：

imshow(clean_img,[min(clean_img(:)), max(clean_img(:))]) 

您会看到您期望看到的所有内容。

一般来说，我通常更喜欢imagesc出于这个原因。 imshow对于代表什么范围做出了任意的判断，而且我通常不会为跟上它而烦恼。我认为在你的情况下，你的最终形象是uint16，所以imshow选择代表范围[1, 65025]。由于所有像素值都低于400，因此它们在该范围内肉眼看起来很黑。