Comparison of DCT and wavelets in image coding

The basic idea of compression is to try to reduce the average number of bits per pixel to adequately represent the image. Image compression is urgently needed for very large medical or satellite images, both for reducing the storage requirements and for improving transmission efficiency. Fourier-based transforms (e.g. DCT and DFT) are efficient in exploiting the low frequency nature of an image. The high frequency coefficients are coarsely quantized, and hence the reconstructed quality of the image at the edges will have poor quality. On the other hand, wavelets are efficient in representing nonstationary signals because of the adaptive time-frequency window. So the Discrete Wavelet Transform (DWT) is applied to an image and the energy compaction performance of both Discrete Cosine Transform (DCT) and DWT is compared. It is observed that both transforms provide comparable energy compaction performance.