uint8 image solarization issue
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Good afternoon I am trying to take a uint8 image and take the complement of all pixels with a grayscale less then 128 and again with all pixels with a grayscale greater than 128. This is an example of my attempt but I don't think it is working properly, if anyone could please give me a hand. I am supposed to create the two functions and then create a small test image to test the functions before applying them to an image but I don't know how to do that.
b=imread('blocks.jpg');
class(b)
comp_light_pixels=b<128 %only complement the lighter pixels of b
subplot(2,2,1)
imshow(comp_light_pixels) %show image with lighter pixels complemented
comp_dark_pixels=b>128 %only complement the darker pixels
subplot(2,2,2)
imshow(comp_dark_pixels) % show image with dark pixels complemented
subplot(2,2,3)
imshow(b) % show original image
subplot(2,2,4)
imshow(255-b) % show completely complemented image
0 件のコメント
回答 (1 件)
Walter Roberson
2018 年 2 月 25 日
comp_light_pixels = b;
mask = comp_light_pixels < 128;
comp_light_pixels(mask) = 255 - comp_light_pixels(mask);
2 件のコメント
DGM
2024 年 6 月 18 日
Granted, it's not like "solarize" is really a well-defined transformation. That said, the given example still doesn't do what's probably expected.
% the image can only be uint8 class
% otherwise, everything will fail
x = uint8(0:255);
% only complement the pixels with grayscales less than 128, or the darker pixels
mask = x < 128;
convert_mask = uint8(mask);
y1 = convert_mask.*x + (1-convert_mask).*(255-x);
% only complement the lighter pixels
mask1 = x > 128;
convert_mask1 = uint8(mask1);
y2 = convert_mask1.*x + (1-convert_mask1).*(255-x);
% plot the curves
plot(x,[y1;y2])
xlim([0 255])
ylim([0 255])
As is common, it's a hard vee curve, but neither case is full swing. That does mean that the contrast is preserved on either side of 50% gray, but I've never seen such an implementation, and have no idea why that would be a desirable interpretation.
This is a far simpler way to do the work. It's a more typical curve, and it's not blindly dependent on the input image class.
% some image in any class
x0 = uint8(0:255);
% put it in a consistent and convenient class and scale
x = im2double(x0);
% interpolate
tf = [0 1 0]; % hard vee curve
%tf = [1 0 1]; % inverted hard vee
y = interp1([0 0.5 1],tf,x,'linear');
% cast the output if you want it in some particular class
y = im2uint8(y);
% plot the curve
plot(x0,y)
xlim([0 255])
ylim([0 255])
The output curve is full swing, as is more typical. The input image can be of any typical numeric class.
% some image in any class
inpict = imread('peppers.png');
% put it in a consistent and convenient class and scale
inpict = im2double(inpict);
% interpolate
tf = [0 1 0]; % hard vee curve
%tf = [1 0 1]; % inverted hard vee
outpict = interp1([0 0.5 1],tf,inpict,'linear');
% cast the output if you want it in some particular class
outpict = im2uint8(outpict);
% display the result
imshow(outpict)
% some image in any class
inpict = imread('peppers.png');
% solarize it (MIMT solarize())
%outpict = solarize(inpict,'vee'); % simple vee curve
outpict = solarize(inpict); % a nonlinear curve
% display the result
imshow(outpict)
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/1718121/image.png)
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