期刊名称：International Journal of Electronics and Computer Science Engineering
电子版ISSN：2277-1956
出版年度：2013
卷号：2
期号：2
页码：763-772
出版社：Buldanshahr : IJECSE
摘要：The main objective of this paper is to focus on three techniques of image compression Burrows Wheeler Transform (BWT), Discrete Cosine Transform (DCT), and Discrete Wavelet Transform (DWT). Image processing systems can encode raw images with different degrees of precision, achieving varying levels of compression. Different encoders with different compression ratios can be built and used for different applications. The need to dynamically adjust the compression ratio of the encoder arises in many applications. One example involves the real-time transmission of encoded data over a packet switched network. To suitably adapt the encoder to varying compression requirements, adaptive adjustments of the compression parameters are required. This involves reconfiguring the encoder in an efficient manner. The main constraint of limitation is the memory of the system. Memory plays a key role in the multimedia devices and the data storage devices, where the images are considerably bulky. The compression ratio in each of the three cases varies which gives the exact idea of how much the image has been compressed. These techniques were implemented using MATLAB and SIMULINK.
