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About 7,733 papers for “wavelet compression”

Wavelet Image Compression

William A. Pearlman · Synthesis lectures on image, video, and multimedia processing · 2013

Cited by 11

Wavelet and wavelet packet compression of electrocardiograms

Michael Hilton · IEEE Transactions on Biomedical Engineering · 1997

Wavelets and wavelet packets have recently emerged as powerful tools for signal compression. Wavelet and wavelet packet-based compression algorithms based on embedded zerotree wavelet (EZW) coding are developed for electrocardiogram (ECG) signals, and eight different wavelets are evaluated for their ability to compress Holter ECG data. Pilot data from a blind evaluation of compressed ECG's by cardiologists suggest that the clinically useful information present in original ECG signals is preserved by 8:1 compression, and in most cases 16:1 compressed ECG's are clinically useful.

Cited by 414

Wavelet-based image compression

Saksena, Shetul · CSUN ScholarWorks (California State University, Northridge) · 2011

Project (M.S., Electrical and Electronic Engineering)--California State University, Sacramento, 2011.

Cited by 0

Enhanced Compression Wavelet (ESW)

JAMISON, JAMIE, YAO, ZHIYUAN · UC Los Angeles · 2021

This dataset contains the Enhanced Compression Wavelet (ESW) data for Los Angeles County, CA in 2017.

Cited by 0Open access

Segmenting for Wavelet Compression

Manu Gupta, A. Stroilov · Data Compression Conference · 2005

Summary form only given. We propose a new approach to segmenting mixed raster content images for compression by wavelet encoders and binary compressors. Though wavelets are efficient at modeling edges in natural images, text and sharp edges can be more effectively represented by a binary mask than with wavelets. A common approach to mixed raster content documents is to segment images from text, and separately compress images and a binary mask that defines the segmentation. We propose that the segmentation be done jointly with a projection-onto-convex-sets (POCS) smoothing, with the design goal of segmented images that have a minimal number of nonzero wavelet coefficients. Our goal is a document segmentation that is easy to compress. Knowing that the image encoder will be a lossy wavelet coder, we approximate the above goal as minimizing the number of nonzero wavelet coefficients. We attempt to achieve this goal by jointly choosing the mask and data-filling.

Cited by 1

INTERPOLATION AND WAVELET COMPRESSION

Richard M. Dansereau, K Kinsner · 1997

This paper presents a perceptual image representation technique based on fractal surface interpolation (FSI). This technique is motivated from the observation that images taken from the real world con- tain many textures that are self-similar, or fractal, in nature. The fractal surface inter- polation representation is then compressed using a zero-tree wavelet compression sub- system with lossless entropy encoding. The fractal surface interpolation technique described relies on the extraction and recon- struction of self-aflne fractal surfaces with measured Hurst exponents H*. This gives statistically self-similar fractal surfaces used to represent textures in a real world image. Fractional Brownian motion (fBm) through a modified midpoint displacement (MPD) algo- rithm provides the basis for generating these self-affine fractal surfaces between interpo- lation points.

Cited by 0

Evolving Wavelet Compression Strategies

Donald Waagen, Jeffrey D. Argast, John R. McDonnell · 1994

Abstract : Wavelet theory provides an attractive approach to signal and image compression. This work investigates a new approach for wavelet transform coefficient selection for efficient image compression. This approach is based on the stochastic optimization of wavelet scale thresholds. Experimental results are compared with results from previously published wavelet image compression strategies. Evolutionary programming, Neural networks, Signal detection.

Cited by 3

Wavelet-based image compression

Chen, Shuran. · DR-NTU (Nanyang Technological University) · 2001

Our study is confined to still and grayscale part of the images. This thesis on the project work consists of three major parts: wavelet theory overview, comparative study, and development of wavelet-based image compression algorithms.

Cited by 0

Adaptive wavelet image compression

Nasir Rajpoot · Warwick Research Archive Portal (University of Warwick) · 2001

Available from British Library Document Supply Centre-DSC:DXN046258 / BLDSC - British Library Document Supply Centre

Cited by 1Open access

Hands-off seismic wavelet compression

Marwan A. Simaan · 2002

Seismic data for imaging the subsurface layers of the Earth are often modeled as a convolution of a source wavelet and a reflectivity sequence of the propagation medium. The process of separating these two signals is called deconvolution. It is often performed by applying a filter that compresses the wavelet to a delta function. Such a filter is estimated using some a priori knowledge of the wavelet. The author shows that this filter can be determined, theoretically, without a priori knowledge of the wavelet and with no assumptions in regards to its statistical properties. Such a process is referred as hands-off deconvolution. The author formulates this as an optimization problem and shows that it can be solved using a constrained least-squares minimization technique. The solution can be shown to reduce to an eigenvalue problem. Several examples will be used to illustrate the result.

Cited by 0

Psychovisually tuned wavelet fingerprint compression

B.G. Sherlock, D.M. Monro · 2002

We present biorthogonal and orthonormal wavelets for embedded zerotree wavelet compression of fingerprint images. By simulated annealing over the wavelet filter coefficients, using a composite cost function dependent upon a parameter k/sup 2/ which weights the relative importance of the wavelet's bandwidth and time dispersion, a series of wavelets is obtained. Each of these is optimal in terms of a particular Heisenberg uncertainty 'footprint', i.e. a particular trade-off between bandwidth and time dispersion. The psychovisually optimal wavelet for fingerprint image compression is determined by fingerprint experts by examination of images compressed and recovered using the series of wavelets. Psychovisually tuned wavelets were found to yield superior visual fidelity to standard wavelets and also to wavelets optimized to produce minimum RMS error on either fingerprint or general test images.

Cited by 13