A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature-Preserving Image Coding for Very Low Bit Rates
DCC '01 Proceedings of the Data Compression Conference
Edge and Mean based Image Compression
Edge and Mean based Image Compression
Feature preserving image compression
Pattern Recognition Letters
Spatial Domain Wavelet Design for Feature Preservation in Computational Data Sets
IEEE Transactions on Visualization and Computer Graphics
Edge Preserving Lossy Image Compression with Wavelets and Contourlets
CERMA '06 Proceedings of the Electronics, Robotics and Automotive Mechanics Conference - Volume 01
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Image compression plays a vital role in multimedia storage and transmission applications. In our work two different approaches of edge preserving lossy image compression are incorporated with the aim of increasing compression ratio and picture quality. An edge image is obtained from the original image using, various edge detectors. The original image is domain transformed using wavelets and preprocessing is being carried out to compress the image. Then the compressed image is reconstructed and the valuable parameter such as Compression Factor and Peak Signal to Noise Ratio are calculated. The performance table is provided in comparison of the two different proposed methods with the existing method of edge preserving image compression for four different standard images and it has been found that proposed method outperforms the existing method in terms of compression ratio and PSNR.