STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Advanced Database Management & Systems

Modified Morphology of Wavelet based Transformations for Color Image Compression

  1. Dipalee Gupta
  2. Siddharth Choubey

Abstract

For the sake of effective transmission and less storage of digital information the signal processing environment requires compression schemes to facilitate easy handling and management of large chunk of information. Such that the redundant data and other chunks of information which can be reproduced from the existing or basic information can be reproduced in no time without requiring large database storages. Wavelet processing is one of such methods which are heavily employed by the researchers in field of signal processing. This mathematical tool enables the encoding of information in hierarchical manner while preserving the approximation for layer wise level of detail. Here, in this study we proposed a wavelet transformation based image compression scheme for color images; while the experimental test are made on contrast preservation for high quality images. The scope of the study is limited to the Harr wavelets with the level order of 3 level decomposition. The quality of the compressed image is evaluated based on parameters like: Peak Signal to Noise Ratio (PSNR), Structural Content (SC), Normalized Absolute Error (NAE) etc. Cite this ArticleDeepalie Gupta, Siddharth Choubey. Modified Morphology of Wavelet based Transformations for Color Image Compression. Journal of Advanced Database Management & Systems. 2015; 2(2): 1–9p.

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