Masking out Images different pixel intensity with different color values

I have a large gray image with size (4329x5448) . I want to color the the pixels depending upon different range of values. My code is:

RGBImage=cat(3,grayImage,grayImage,grayImage);

for ii=1:size(grayImage,1)

for jj=1:size(grayImage,2)

% get pixel value

pixel=RGBImage(ii,jj,1);

if(~isnan(pixel))

% check pixel value and assign new value

if pixel>0 && pixel<=0.2

new_pixel=[0; 0; 1];

elseif pixel>0.2 && pixel<=0.4

new_pixel=[0; 1; 0];

elseif pixel>0.4 && pixel<=0.6

new_pixel=[1; 1; 0];

elseif pixel>0.6 && pixel<=0.8

new_pixel=[1; 0; 0];

else

new_pixel = [0; 0; 0];

end

% save new pixel value in thresholded image

RGBthreshold(ii,jj,:)=new_pixel;

else

RGBthreshold(ii,jj,:)=[NaN;NaN;NaN];

end

end

end

But the code is slow. It is taking long time. Any idea of making it fast.

Answer 1

[DGM]

Don't do it pixel by pixel. That'll take forever. At most, do it channel by channel or frame by frame. There are a lot of ways to do something like this. I'm going to choose to do it in a fairly basic and direct way.

% this is just my test image; not included
inpict=imread('sources/table.jpg');
graypict=im2double(rgb2gray(inpict));

% we want how many gray levels
graylevels=5;
% what's our colormap? 
cmap=[0 0 1; 0 1 0; 1 1 0; 1 0 0; 0 0 0];
% number of graylevels should correspond to the length of cmap

% get map of nans
nanmap=isnan(graypict);

% allocate output array
outpict=zeros([size(graypict,1) size(graypict,2) 3]);
% permute the colormap
cmap=permute(cmap,[1 3 2]);
for gl=1:graylevels
	% make a logical mask for this range of gray values
	mask=(graypict>=((gl-1)/graylevels)) & (graypict<=(gl/graylevels));
	
	% step through the image channels and assign color values to the mask region
	% this can be done with bsxfun, but let's not get confusing.
	for c=1:3
		thischannel=outpict(:,:,c);
		thischannel(mask)=cmap(gl,1,c);
		outpict(:,:,c)=thischannel;
	end
end

% inherit all those wonderful NaNs
for c=1:3
	thischannel=outpict(:,:,c);
	thischannel(nanmap)=NaN;
	outpict(:,:,c)=thischannel;
end

imshow(outpict)

It's not going to win any awards for efficiency or elegance, but it's readable. It takes about 9 seconds to process a 4500x5500 image on a ~10 year old computer.

The per-channel loops could be avoided with bsxfun and/or array replication. The MIMT (on the file exchange) has a multilevel mask generation tool (mlmask()) and a tool for replacing image regions with a color tuple based on a single-channel mask (replacepixels()). There are probably other ways.