1. 简单图像处理
加载图像 Brain.jpg，使用直方图和颜色分割成区域这些区域有不同的颜色。 这是一个更高级的问题，有多个解决它的方法。
例如，您可以计算具有特定数字的图像的直方图（例如 16 - 32），找到直方图中最小值的位置（参见，例如，islocalmin）并对最小值之间的强度区域应用不同的颜色。这可以通过将强度值作为颜色查找表的索引来完成（例如 hsv 生成）并将强度值重新映射到此类（请参阅 ind2rgb）。 您可以还可以通过灰度强度来缩放颜色的强度。
2. MATLAB 源码
matlab
% Load and show image
im = imread('brain.jpg');
im = rgb2gray(im);
figure(1);
clf;
subplot(1,3,1);
imshow(im);
% Histogram
bins = 24;
subplot(1,3,2);
[counts,idx] = imhist(im,bins);
plot(idx,counts);
axis tight;
% Find minima and make sure they are integers
minima = round(idx(islocalmin(counts))');
xline(minima);
% Color regions by mapping greyscale to colormap indices
colors = hsv(numel(minima)+1); % HSV colormap for base-color for region (over hue values only)
cc = 1;
p = 0;
map = zeros(256,3);
for l = [minima, 256] % cover index (intensity) ranges from p to l, including the last one to 256
cidx = (p+1):l;
for k = cidx % Loop for simplicity (instead of matrix operation)
%map(k,:) = colors(cc,:); % No scaling w.r.t original itensity
%map(k,:) = colors(cc,:) * k/256; % Linearly scale color value w.r.t. original intensity
map(k,:) = colors(cc,:) * (0.25 + (k-p-1)/(l-p-1)*0.75); % Different color itensity scaling
end
p = l;
cc = cc + 1;
end
imc = ind2rgb(im,map);
subplot(1,3,3);
imshow(imc);
% Show ranges in histogram by overlaying colors (could be integrated in above loop)
subplot(1,3,2);
y1 = 0;
y2 = max(counts);
cc = 1;
p = 0;
for l = [minima,256]
h = rectangle('Position', [p, 0, l-p, y2], ...
'FaceColor', [colors(cc,:),0.3], ...
'EdgeColor', [colors(cc,:),0.3]);
p = l;
cc = cc + 1;
end3. 输出结果
脑切片图像分割结果
