A New Adaptive Spatial Filtering Method in the Wavelet Domain for Medical Images

Although there are many methods in the literature to eliminate noise from images, finding new methods remains a challenge in the field and, despite the complexity of existing methods, many of the methods do not reach a sufficient level of applicability, most often due to the relatively high calculat...

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Bibliographic Details
Published inApplied sciences Vol. 10; no. 16; p. 5693
Main Authors Simona Răboacă, Maria, Dumitrescu, Cătălin, Filote, Constantin, Manta, Ioana
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.08.2020
Subjects
Adaptive filters
adaptive spatial filter
Algorithms
Computer applications
Domains
hierarchical correlation map
Lagrange multiplier
Medical imaging
Methods
Noise
noise reduction
Principal components analysis
Spatial filtering
wavelet domain
wavelet functions
Wavelet transforms
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Summary:Although there are many methods in the literature to eliminate noise from images, finding new methods remains a challenge in the field and, despite the complexity of existing methods, many of the methods do not reach a sufficient level of applicability, most often due to the relatively high calculation time. In addition, most existing methods perform well when the processed image is adapted to the algorithm, but otherwise fail or results in significant artifacts. The context of eliminating noise from images is similar to that of improving images and for this reason some notions necessary to understand the proposed method will be repeated. An adaptive spatial filter in the wavelet domain is proposed by soft truncation of the wavelet coefficients with threshold value adapted to the local statistics of the image and correction based on the hierarchical correlation map. The filter exploits, in a new way, both the inter-band and the bandwidth dependence of the wavelet coefficients, considering the minimization of computational resources.
ISSN:2076-3417
2076-3417
DOI:10.3390/app10165693