K-means on a gray scale image
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Iremsu Savas
am 24 Okt. 2018
Kommentiert: Image Analyst
am 2 Sep. 2020
Hello everyone, I have a grayscale image 'lena.bmp' and I am trying to apply k-means color quantization. I found the following code but I have some points that are not clear in my mind: 1)Why we need to convert the image format to double? 2)While I am writing "pixel_labels = reshape(cluster_idx,nrows,ncols);" in the code what excatly it is doing? 3)Why did I need to write the square brackets inside this "imshow(pixel_labels,[])" ? The code is here:
Image=imread('lena.bmp');
Image = im2double(Image);
nrows = size(Image,1);
ncols = size(Image,2);
Image = reshape(Image,nrows*ncols,1);
Colors = 4;
[cluster_idx, cluster_center] = kmeans(Image,Colors,'distance','sqEuclidean');
pixel_labels = reshape(cluster_idx,nrows,ncols);
imshow(pixel_labels,[]);
Thank you so much.
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Adam
am 24 Okt. 2018
1. kmeans only supports double or single inputs. It works in floating point so integers wouldn't make sense.
2.
doc reshape
will answer this. It does pretty much exactly what it says - it reshapes your output back to the number of rows and columns of your image so that you have an image back rather than just a vector of class indices.
3.
doc imshow
describes the different scaling you can do with imshow. This syntax is the 3rd in the list.
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Image Analyst
am 24 Okt. 2018
See my attached demos for kmeans in both color and grayscale. Write back if you still have questions.
By the way, you can't do "color quantization" on a grayscale image, unless you're considering the gray levels as "colors".
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Mnahil Khursheed
am 1 Sep. 2020
How to save the result of segmentation is a folder for feature extraction further. Any one please help me.
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