A MODIFIED EMBEDDED ZERO-TREE WAVELET METHOD FOR MEDICAL IMAGE COMPRESSION
Journal: ICTACT Journal on Image and Video Processing (IJIVP) (Vol.1, No. 2)Publication Date: 2010-11-01
Authors : T. Celine Therese Jenny; G. Muthu Lakshmi;
Page : 87-91
Keywords : Image Compression; Embedded Zero-Tree Wavelet; PNG; BMP; Vector Quantization; Entropy Coder; Image Compression; Self Organizing Feature Map;
Abstract
The Embedded Zero-tree Wavelet (EZW) is a lossy compression method that allows for progressive transmission of a compressed image. By exploiting the natural zero-trees found in a wavelet decomposed image, the EZW algorithm is able to encode large portions of insignificant regions of an still image with a minimal number of bits. The upshot of this encoding is an algorithm that is able to achieve relatively high peak signal to noise ratios (PSNR) for high compression levels. The EZW algorithm is to encode large portions of insignificant regions of an image with a minimal number of bits. Vector Quantization (VQ) method can be performed as a post processing step to reduce the coded file size. Vector Quantization (VQ) method can be reduces redundancy of the image data in order to be able to store or transmit data in an efficient form. It is demonstrated by experimental results that the proposed method outperforms several well-known lossless image compression techniques for still images that contain 256 colors or less.
Other Latest Articles
- DEVELOPMENT OF 2D HUMAN BODY MODELING USING THINNING ALGORITHM
- OPTIMAL LEVEL OF DECOMPOSITION OF STATIONARY WAVELET TRANSFORM FOR REGION LEVEL FUSION OF MULTI-FOCUSED IMAGES
- FAST DISCRETE CURVELET TRANSFORM BASED ANISOTROPIC FEATURE EXTRACTION FOR IRIS RECOGNITION
- A SWITCHING ALGORITHM USING MODIFIED SELECTION SORT FOR THE REDUCTION OF IMPULSE NOISE
- ROBUSTNESS OF A FACE-RECOGNITION TECHNIQUE BASED ON SUPPORT VECTOR MACHINES
Last modified: 2013-12-03 20:06:48