calibration in image analysis

Question

Chaitanya kumar reddy 2022-10-4

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1817535-calibration-in-image-analysis

回答： Udit06 2023-9-29

find (BW==1);

[m,n]= find (BW==1);

pos = [m';n'];

D = zeros(1,448)

for i = 1:length(m)

i

D(i,:) = [calibrated_data(m(i),n(i),:)]

end

i have used the above code for calibration but the dataset has 398656 elements and it is taking so long to calibrate like more than 1hr. is there any faster way for calibration??

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Benjamin Thompson 2022-10-4

Can you provide more information about what you are calibrating, and maybe a small sample image? What is the problem?

Chaitanya kumar reddy 2022-10-4

clc

clear all

close all

dataset_name = ['20220118_test_Normalbreast_061722_1_left_2022-06-17_19-28-26'];

raw_data_headfile = strcat('D:\HSI_data\', dataset_name, '\capture\', dataset_name, '.hdr');

raw_data_datafile = strcat('D:\HSI_data\', dataset_name, '\capture\', dataset_name, '.raw');

dark_ref_headfile = strcat('D:\HSI_data\', dataset_name, '\capture\DARKREF_', dataset_name, '.hdr');

dark_ref_datafile = strcat('D:\HSI_data\', dataset_name, '\capture\DARKREF_', dataset_name, '.raw');

white_ref_headfile = strcat('D:\HSI_data\', dataset_name, '\capture\WHITEREF_', dataset_name, '.hdr');

white_ref_datafile = strcat('D:\HSI_data\', dataset_name, '\capture\WHITEREF_', dataset_name, '.raw');

raw_info = enviinfo(raw_data_headfile);

raw_data = multibandread(raw_data_datafile,[raw_info.Height, raw_info.Width, raw_info.Bands],...

raw_info.DataType, raw_info.HeaderOffset, raw_info.Interleave, raw_info.ByteOrder);

dark_info = enviinfo(dark_ref_headfile);

dark_data = multibandread(dark_ref_datafile, [dark_info.Height, dark_info.Width, dark_info.Bands],...

dark_info.DataType, dark_info.HeaderOffset, dark_info.Interleave, dark_info.ByteOrder);

dark_data_avg = mean(dark_data, 1);

white_info = enviinfo(white_ref_headfile);

white_data = multibandread(white_ref_datafile, [white_info.Height, white_info.Width, white_info.Bands],...

white_info.DataType, white_info.HeaderOffset, white_info.Interleave, white_info.ByteOrder);

white_data_avg = mean(white_data, 1);

calibrated_data = raw_data;

for i = 1:size(raw_data, 1)

calibrated_data(i, :, :) = (calibrated_data(i, :, :) - dark_data_avg)./ (white_data_avg - dark_data_avg);

end

rice_dot = calibrated_data(238, 460, :);

background_dot = calibrated_data(323, 658, :);

plot(raw_info.Wavelength, rice_dot(:))

hold on

plot(raw_info.Wavelength, background_dot(:))

legend('grape', 'background')

A = imread('D:\HSI_data\20220118_test_Normalbreast_061722_1_left_2022-06-17_19-28-26\20220118_test_Normalbreast_061722_1_left_2022-06-17_19-28-26.png');

imshow(A)

B = rgb2gray(A);

level = graythresh(B);

BW = im2bw(B,level);

find (BW==1);

[m,n]= find (BW==1);

pos = [m';n'];

D = zeros(1,448)

%D = cell([1 2]);

for i = 1:length(m)

D(i,:) = [calibrated_data(m(i),n(i),:)];

end

% E = mean(D);

% plot(raw_info.Wavelength,E)

% figure

% imshow(BW);

%

% % D = calibrated_data(70,275,:);

% % E = reshape(D,[1,448]);

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Answer 1

Udit06 2023-9-29

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1817535-calibration-in-image-analysis#answer_1321564

Hi Chaitanya,

I understand that the code that you have written for calibration is taking a long time to run. You can utilize the following features supported by MATLAB to make your code run faster.

1) Vectorization: Instead of using a loop to iterate over each element, try to use vectorized operations whenever possible. MATLAB is optimized for array operations, and using vectorization can significantly speed up the computation.

2) Parallel Computing: Consider using parallel computing techniques like MATLAB's "parfor" to distribute the workload across multiple workers.

You can refer to the below MathWorks documentations to understand more about vectorization and “parfor” respectively.

1) https://www.mathworks.com/help/matlab/matlab_prog/vectorization.html searchHighlight=vectorization&s_tid=srchtitle_support_results_1_vectorization

2) https://www.mathworks.com/help/parallel-computing/parfor.html

I hope this helps.