文件名称:yanyan
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把一个256*256的图像分成8*8小块,然后进行DFT变换,分别比较在空间域和频域内对图像进行二次抽样和差值最后得出的图像比较-1. Get a grey level image which size is N*N. (For example, 256*256, however,
N = ), and partition to 8*8 sub images.
2. Apply DFT to these sub images, and get the fourier transformed image F.
3. Derive the proper subsampling function matrix S in spatial domain.
4. Multiplying proper 4*4 DFT matrix T to matrix S, derive the frequency version
of subsampling function matrix, S.
5. Similarly, derive the frequency version of interpolation matrix, I.
6. Apply these matrices to each sub image of F (which is DFT of original image),
and get the final image, taking inverse DFT.
7. Apply subsampling/interpolation function matrix S/I to original image in spatial
domain and get the final image.
8. Compare the results from 6, 7.
N = ), and partition to 8*8 sub images.
2. Apply DFT to these sub images, and get the fourier transformed image F.
3. Derive the proper subsampling function matrix S in spatial domain.
4. Multiplying proper 4*4 DFT matrix T to matrix S, derive the frequency version
of subsampling function matrix, S.
5. Similarly, derive the frequency version of interpolation matrix, I.
6. Apply these matrices to each sub image of F (which is DFT of original image),
and get the final image, taking inverse DFT.
7. Apply subsampling/interpolation function matrix S/I to original image in spatial
domain and get the final image.
8. Compare the results from 6, 7.
相关搜索: inverse image function
图像比较
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