The IUP Journal of Telecommunications
Three-Dimensional Image Compression Using 2.5D Spatial Subsampling and Reconstruction Using 2.5D Morphological Filters

Article Details
Pub. Date : Feb, 2019
Product Name : The IUP Journal of Telecommunications
Product Type : Article
Product Code : IJTC31902
Author Name : Trupti Ahir and R V S Satyanarayana
Availability : YES
Subject/Domain : Science & Technology
Download Format : PDF Format
No. of Pages : 14



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.


Image compression has been the topic of interest for many years. The necessity for compressing digital images has evolved mainly from media applications where a large amount of image data is acquired, stored, processed and transmitted over varieties of channels. This necessity has been intensified especially after the advent of high definition image transactions, especially in medical image applications like MRI data processing and high definition digital video production, storage and transmission. With the idea of catering to the needs of image compression, efforts were made in academic institutions, research centers and industries to compress large image data for storage and transmission using various coding techniques and image reconstruction using decoding techniques, of course without incurring much loss of information.


Spatial sparsing, Morphological filters, Rectangular sub-sampling, 3D image compression

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