William A Pearlman | Search PubMed

PubMed2006

A wavelet-based two-stage near-lossless coder.

In this paper, we present a two-stage near-lossless compression scheme. It belongs to the class of "lossy plus residual coding" and consists of a wavelet-based lossy layer followed by arithmetic coding of the quantized residual to guarantee a given L(infinity) error bound in the pixel domain. We focus on the selection of the optimum bit rate for the lossy layer to achieve the minimum total bit rate. Unlike other similar lossy plus lossless approaches using a wavelet-based lossy layer, the proposed method does not require iteration of decoding and inverse discrete wavelet transform in succession to locate the optimum bit rate. We propose a simple method to estimate the optimal bit rate, with a theoretical justification based on the critical rate argument from the rate-distortion theory and the independence of the residual error.

Algorithms↗

PubMed2004

Lossless compression of volumetric medical images with improved three-dimensional SPIHT algorithm.

This article presents a lossless compression of volumetric medical images with the improved three-dimensional (3-D) set partitioning in hierarchical tree (SPIHT) algorithm that searches on asymmetric trees. The tree structure links wavelet coefficients produced by 3-D reversible integer wavelet transforms. Experiments show that the lossless compression with the improved 3-D SPIHT gives improvement about 42% on average over two-dimensional techniques and is superior to those of prior results of 3-D techniques. In addition, we can easily apply different numbers of decomposition between the transaxial and axial dimensions, which is a desirable function when the coding unit of a group of slices is limited in size.

Adolescent↗

PubMed2003

Region-based wavelet coding methods for digital mammography.

Spatial resolution and contrast sensitivity requirements for some types of medical image techniques, including mammography, delay the implementation of new digital technologies, namely, computer-aided diagnosis, picture archiving and communications systems, or teleradiology. In order to reduce transmission time and storage cost, an efficient data-compression scheme to reduce digital data without significant degradation of medical image quality is needed. In this study, we have applied two region-based compression methods to digital mammograms. In both methods, after segmenting the breast region, a region-based discrete wavelet transform is applied, followed by an object-based extension of the set partitioning in hierarchical trees (OB-SPIHT) coding algorithm in one method, and an object-based extension of the set partitioned embedded block (OB-SPECK) coding algorithm in the other. We have compared these specific implementations against the original SPIHT and the new standard JPEG 2000, both using reversible and irreversible filters, on five digital mammograms compressed at rates ranging from 0.1 to 1.0 bit per pixel (bbp). Distortion was evaluated for all images and compression rates by the peak signal-to-noise ratio. For all images, OB-SPIHT and OB-SPECK performed substantially better than the traditional SPIHT and JPEG 2000, and a slight difference in performance was found between them. A comparison applying SPIHT and the standard JPEG 2000 to the same set of images with the background pixels fixed to zero was also carried out, obtaining similar implementation as region-based methods. For digital mammography, region-based compression methods represent an improvement in compression efficiency from full-image methods, also providing the possibility of encoding multiple regions of interest independently.

Algorithms↗