|Communications on Applied Electronics|
|Foundation of Computer Science (FCS), NY, USA|
|Volume 2 - Number 8|
|Year of Publication: 2015|
|Authors: Arvind Kumar, Arun Uniyal, Pawan Kumar|
Arvind Kumar, Arun Uniyal, Pawan Kumar . Comparative Analysis of DWT and DCT Image Compressions Techniques using VHDL. Communications on Applied Electronics. 2, 8 ( September 2015), 20-24. DOI=10.5120/cae2015651828
Image compression is very important part of the digital image processing. Image compression is the method of reducing the size of image, which is helpful to increase the storage and transmission performance. In the compression method not only concentrate on reducing the size of image, but also concentrate on the quality and information of the image. Image compressions have more researched area, and many compression standards are place. But still here there is a scope for high compression quality; the JPEG and JPEG2000 standard make use of Discrete cosine transform DCT and Discrete Wavelet transform DWT for compression respectively. Discrete wavelet and Discrete cosine transforms are the common method used in image compression. Wavelet transform are very powerful as compared to Fourier transform, because it have ability to describe any type of signals both in time and frequency domain simultaneously. In this thesis two image compression methods are simulated, the first method is based on Discrete Wavelet transform (DWT), and second method is based on Discrete Cosine transform (DCT). The aim of the thesis as to compress an image using DWT and DCT encoding method, to implement DWT and DCT using VHDL and measure the performance in terms of memory utilization and timing parameters. The first part of the thesis presents an implementation of Discrete Wavelet Transform with HAAR Wavelet and the second part of the thesis presents an implementation of Discrete Cosine Transform. The performance will be measured in term of memory utilization and timing parameters.