The discrete cosine transform (DCT) helps separate the image into parts (or spectral sub-bands) of differing importance (with respect to the image's visual quality). The DCT is similar to the discrete Fourier transform: it transforms a signal or image from the spatial domain to the frequency domain.
The basic operation of the DCT is as follows:
1. The input image is N by M;
2. f(i,j) is the intensity of the pixel in row i and column j;
3. F(u,v) is the DCT coefficient in row k1 and column k2 of the DCT matrix.
4. For most images, much of the signal energy lies at low frequencies; these appear in the upper left corner of the DCT.
5. Compression is achieved since the lower right values represent higher frequencies, and are often small - small enough to be neglected with little visible distortion.
6. The DCT input is an 8 by 8 array of integers. This array contains each pixel's gray scale level;
7. 8 bit pixels have levels from 0 to 255.
The basic operation of the DCT is as follows:
1. The input image is N by M;
2. f(i,j) is the intensity of the pixel in row i and column j;
3. F(u,v) is the DCT coefficient in row k1 and column k2 of the DCT matrix.
4. For most images, much of the signal energy lies at low frequencies; these appear in the upper left corner of the DCT.
5. Compression is achieved since the lower right values represent higher frequencies, and are often small - small enough to be neglected with little visible distortion.
6. The DCT input is an 8 by 8 array of integers. This array contains each pixel's gray scale level;
7. 8 bit pixels have levels from 0 to 255.
No comments:
Post a Comment