Convert matrix to grayscale image
I = mat2gray(A,[amin amax])
I = mat2gray(A)
converts the matrix
I = mat2gray(
A to an intensity image
I that contains values in the range 0 (black) to 1 (white).
amax are the values in
A that correspond to 0 and 1 in
Values less than
amin become 0, and values greater than
amax become 1.
You optionally can perform the operation using a GPU (requires Parallel Computing Toolbox™). For more information, see Image Processing on a GPU.
Read an image and display it.
I = imread('rice.png'); figure imshow(I)
Perform an operation that returns a numeric matrix. This operation looks for edges.
J = filter2(fspecial('sobel'),I); min_matrix = min(J(:))
min_matrix = -779
max_matrix = max(J(:))
max_matrix = 560
Note that the matrix has data type
double with values outside of the range [0,1], including negative values.
Display the result of the operation. Because the data range of the matrix is outside the default display range of
imshow, every pixel with a positive value displays as white, and every pixel with a negative or zero value displays as black. It is challenging to see the edges of the grains of rice.
Convert the matrix into an image. Display the maximum and minimum values of the image.
K = mat2gray(J); min_image = min(K(:))
min_image = 0
max_image = max(K(:))
max_image = 1
Note that values are still data type
double, but that all values are in the range [0, 1].
Display the result of the conversion. Pixels show a range of grayscale colors, which makes the location of the edges more apparent.
A— Input image
Input image, specified as a numeric matrix.
To perform the computation using a GPU, specify
gpuArray that contains a
[amin amax]— Input black and white values
This function fully supports GPU arrays. For more information, see Image Processing on a GPU.