Authors:
Aura Conci
1
;
Marcello Santos Fonseca
1
;
Carlos S. Kubrusly
2
and
Thomas Walter Raubert
3
Affiliations:
1
Institute of Computation, UFF, Brazil
;
2
Electrical Engineering Department, PUC-RJ, Brazil
;
3
Department of Informatic, UFES, Brazil
Keyword(s):
Compression-denoising, Additive White Gaussian Noise, Image Filtering, Wavelet Family, Haar’s Wavelet, Daubechies’ Wavelet, Biorthogonal Wavelet, Coiflet Wavelet, Symlet Wavelet.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Enhancement and Restoration
;
Image and Video Analysis
;
Image Filtering
;
Image Formation and Preprocessing
;
Wavelet Analysis
Abstract:
Uncompressed multimedia data such as high resolution images, audio and video require a considerable storage capacity and transmission bandwidth on telecommunications systems. Despite of the development of the storage technology and the high performance of digital communication systems, the demand for huge files is higher than the available capacity. Moreover, the growth of image data in database applications needs more efficient ways to encode images. So image compression is more important than ever. One of the most used techniques is compression by wavelet, specified in the JPEG 2000 standard and recommended also for medical image DICOM database. This work seeks to investigate the wavelet image compression-denoising technique related to the wavelet family bases used (Haar, Daubechies, Biorthogonal, Coiflets and Symlets), database content and noise level. The target of the work is to define which combination present the best and the worst compression quality, through quality evaluati
on by quantitative functions: Root Mean Square Error (RMSE), Sign Noise Ratio (SNR) and Peak Sign Noise Ratio (PSNR).
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