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Discrete Cosine Transform

The DCT is fast to calculate and is optimal for images that are highly correlated. Unlike the Fourier Transform, the DCT is all real, which means that for an image, we will also have image001.jpg coefficients. Like the Fourier Transform, the DCT provides a 1-to-1 mapping. Therefore, to get back the original image, we simply take the IDCT of the our transformed image. We can find the DCT by using the following formula:

image002.jpg

where image003.jpg and C(u) = 1 for image004.jpg . DCT images typically look like the following:
   image005.jpg
Figure: DCT image.

The bright regions correspond to big coefficients and the black regions correspond to small coefficients. If we then divide the image into a number of small blocks, we can allocate bits for each block, where the blocks on the top left corner would be encoded with many bits, and the ones at the bottom right corner would be coded with few or no bits. The allocation of encoding bits is distributed by means of a mask. We divide the DCT into 16x16 blocks and all the coefficients of the block is encoded with the same number of bits.


next up previous
Next: Wavelet Transforms Up: Transform coding Previous: Transform coding
Andrew Doran
Cherry Wang
Huipin Zhang
1999-04-14