Difference between dct and dft in image processing

The difference between the two is the type of basis function used by each transform; the DFT uses a set of harmonically-related complex exponential functions, while the DCT uses only (real-valued) cosine functions.

1. What is the difference between DCT and DFT?
2. Why is DCT better than DFT?
3. Is DCT real part of DFT?
4. Why DCT is preferred for image processing?

What is the difference between DCT and DFT?

Like the discrete Fourier transform (DFT), a DCT operates on a function at a finite number of discrete data points. The obvious distinction between a DCT and a DFT is that the former uses only cosine functions, while the latter uses both cosines and sines (in the form of complex exponentials).

Why is DCT better than DFT?

> DCT is preferred over DFT in image compression algorithms like JPEG > because DCT is a real transform which results in a single real number per > data point. In contrast, a DFT results in a complex number (real and > imaginary parts) which requires double the memory for storage.

Is DCT real part of DFT?

DCT is NOT the real part of the DFT rather it is related to the DFT of a symmetrically extended signal/image. The energy of signal/image is packed mostly in only a few DCT coefficients (i.e. only a few significant X(k)'s), hence making DCT very useful for data compression applications.

Why DCT is preferred for image processing?

1) The DCT is real-valued instead of complexity (i.e., it involves magnitude and phase) such that it is easier to be implemented. 2) The DCT is more efficient for illumination variation estimation than the DWT. 3) The DCT approach is similar to the homomorphic filtering, which has been used for contrast enhancement.