Three-Dimensional Image Compression Using 2.5D Spatial Subsampling and Reconstruction Using 2.5D Morphological Filters

Three-dimensional image compression is an important requirement in 3D medical imaging applications. The paper describes a novel approach to compress a 3D image to 25% and reconstruct it so that the reconstructed image is almost close to the original image. Spatial sparsing is used to subsample every...

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Bibliographic Details
Published in:IUP journal of telecommunications 2019-02, Vol.11 (1), p.22-35
Main Authors: Ahir, Trupti, Satyanarayana, R V S
Format: Article
Language:English
Subjects:
Algorithms
Biomedical engineering
Data compression
Fourier transforms
Image compression
Image filters
Image reconstruction
International conferences
Medical imaging
Morphological filters
Morphology
Noise
Signal processing
Sparsity
Three dimensional imaging
Wavelet transforms
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Summary:Three-dimensional image compression is an important requirement in 3D medical imaging applications. The paper describes a novel approach to compress a 3D image to 25% and reconstruct it so that the reconstructed image is almost close to the original image. Spatial sparsing is used to subsample every slice of a given 3D image, and slice-wise reconstruction is carried out using certain morphological filters. This technique is called 2.5D compression of 3D images.
ISSN:0975-5551