An efficient image compression technique using discrete wavelet transform (DWT)

Abstract

Designing Universal embedded hardware architecture for discrete wavelet transform is a challenging problem because of diversity among wavelet kernel filters. In this work, DWT is used for compression application. Wavelet transform divides the information of an image into approximation and details sub signals. The approximation sub signals shows the general trend of pixel values and other three detail sub signals show the vertical, horizontal and diagonal details or changes in the images. If these details are very small (threshold) then they can be set to zero without significantly changing the image. The greater the number of zeros the greater the compression ratio. If the energy retained (amount of retained by an image after compression and decompression) is 100% then the compression is lossless as the image can be reconstructed exactly. The design follows the JPEG2000 standard and can be used for both lossy and lossless compression. The High-performance and memory-efficient pipeline architecture which performs the one-level (2-D) DWT in the 5/3 and 9/7 filters.