image compression using FFT
16 ビュー (過去 30 日間)
古いコメントを表示
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..
0 件のコメント
回答 (2 件)
Walter Roberson
2014 年 4 月 3 日
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.
0 件のコメント
sam k
2020 年 6 月 6 日
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 件のコメント
Sulaymon Eshkabilov
2023 年 11 月 15 日
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
参考
カテゴリ
Help Center および File Exchange で Denoising and Compression についてさらに検索
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!