image compression using FFT

14 vues (au cours des 30 derniers jours)
Jitesh Bhanushali
Jitesh Bhanushali le 3 Avr 2014
Sir how can we compress image using FFT transform..RLE coding is not suitable with the FFT..what coding technique is suitable for FFT to compress the image..

Réponses (2)

Walter Roberson
Walter Roberson le 3 Avr 2014
RLE is a lossless compression technique. Compression with FFT is a lossy compression technique. You do the FFT, and you throw away some of the coefficients and output the rest; then for reconstruction you let the missing coefficients be 0 and do the inverse FFT.
Which coefficients you should throw away is something for you to explore.

sam k
sam k le 6 Juin 2020
a=imread('link.jpeg');
grayIm =rgb2gray(a);
[row col] = size(grayIm);
subplot(2, 2, 1);
imshow(grayIm);
title('original image')
A=fft2(grayIm); %2D fft
count_pic=2;
for thresh=0.1*[0.001 0.005 0.006]*max(max(abs(A)))
ind=abs(A)>thresh;
count=row*col-sum(sum(ind));
Alow=A.*ind;
per=100-count/(row*col)*100;
Blow=uint8(ifft2(Alow));
subplot(2,2,count_pic);
imshow(Blow);
count_pic=count_pic+1;
title([num2str(per) '% of fft basis'])
end
  2 commentaires
Thinh
Thinh le 26 Oct 2022
can you explain this, please
Sulaymon Eshkabilov
Sulaymon Eshkabilov le 15 Nov 2023
This means what % of the highest FFT coeffcients to keep.
It can be also applied for color (RGB) images as well:
A = imread('A1.jpeg');
Afft=fft2(A);
Asort = sort(abs(Afft(:)));
counter=0;
for Keep = [.95 .1 .05 .001]
threshold = Asort(floor((1-Keep)*length(Asort)));
Ind = abs(Afft)>threshold;
Atlow = Afft.*Ind;
Alow = uint8(ifft2(Atlow));
s = whos('Alow');
totSize = s.bytes;
counter=counter+1;
figure(counter)
imshow(Alow)
saveas(gcf, strcat(['FFT_IMG', num2str(counter) '.jpeg']))
s = dir(strcat(['FFT_IMG', num2str(counter) '.jpeg']));
filesize(counter)=s.bytes
title([num2str(Keep) '% of fft basis is kept and updated image file size is: ' num2str(s.bytes)])
end

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