World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
41
Citations
18595
World Ranking
8572
National Ranking
3668

Research.com Recognitions

  • 1998 - IEEE Fellow For contributions to the theory and practice of source coding and image compression.
  • 1990 - SPIE Fellow

Overview

William A. Pearlman is affiliated with Rensselaer Polytechnic Institute in the United States. Their research domain spans several fields within science and engineering, with a focus on computer science, engineering, and mathematics.

The main fields of study in which William A. Pearlman has contributed are:

  • Computer Science (15 publications)
  • Engineering (2 publications)
  • Mathematics (1 publication)

Within these fields, their work explores a number of subfields, notably:

  • Computer Vision and Pattern Recognition (9 publications)
  • Signal Processing (4 publications)
  • Artificial Intelligence (2 publications)
  • Applied Mathematics (1 publication)
  • Civil and Structural Engineering (1 publication)

The topics of William A. Pearlman's research include a variety of technical and applied areas, such as:

  • Image and Signal Denoising Methods (12 publications)
  • Digital Filter Design and Implementation (8 publications)
  • Advanced Data Compression Techniques (6 publications)
  • Neural Networks and Applications (4 publications)
  • Statistical and numerical algorithms (2 publications)
  • Structural Health Monitoring Techniques (2 publications)
  • Control Systems and Identification (2 publications)

Among published works, William A. Pearlman has contributed a book through Morgan & Claypool Publishers titled Mathematical Transformations and Wavelet Filters for Source Coding and Signal Processing Systems, published in 2023.

Professional recognitions include being named an IEEE Fellow in 1998 for contributions to the theory and practice of source coding and image compression. Additionally, they hold the distinction of SPIE Fellow since 1990.

Best Publications

  • A new, fast, and efficient image codec based on set partitioning in hierarchical trees

    A. Said;W.A. Pearlman

  • An image multiresolution representation for lossless and lossy compression

    A. Said;W.A. Pearlman

  • Low bit-rate scalable video coding with 3-D set partitioning in hierarchical trees (3-D SPIHT)

    Beong-Jo Kim;Zixiang Xiong;W.A. Pearlman

  • Wavelet compression of ECG signals by the set partitioning in hierarchical trees algorithm

    Zhitao Lu;Dong Youn Kim;W.A. Pearlman

  • Steganalysis of additive-noise modelable information hiding

    Jeremiah Joseph Harmsen;William A. Pearlman

  • Efficient, low-complexity image coding with a set-partitioning embedded block coder

    W.A. Pearlman;A. Islam;N. Nagaraj;A. Said

  • An embedded wavelet video coder using three-dimensional set partitioning in hierarchical trees (SPIHT)

    Beong-Jo Kim;W.A. Pearlman

  • Embedded and efficient low-complexity hierarchical image coder

    Asad Islam;William A. Pearlman

  • Image compression using the spatial-orientation tree

    A. Said;W.A. Pearlman

  • SPIHT image compression without lists

    F.W. Wheeler;W.A. Pearlman

  • Low-complexity waveform coding via alphabet and sample-set partitioning

    Amir Said;William A. Pearlman

  • Data compression using set partitioning in hierarchical trees

    William Abraham Pearlman;Amir Said

  • Reversible image compression via multiresolution representation and predictive coding

    Amir Said;William A. Pearlman

  • Three-Dimensional Wavelet-Based Compression of Hyperspectral Images

    Xiaoli Tang;William A. Pearlman

  • Three-dimensional subband coding of video using the zero-tree method

    Yingwei Chen;William A. Pearlman

  • Speckle filtering of SAR images based on adaptive windowing

    J.-M. Park;W.J. Song;W.A. Pearlman

  • Region-based wavelet coding methods for digital mammography

    M. Penedo;W.A. Pearlman;P.G. Tahoces;M. Souto

  • A full-featured, error-resilient, scalable wavelet video codec based on the set partitioning in hierarchical trees (SPIHT) algorithm

    Sungdae Cho;W.A. Pearlman

  • Hyperspectral Image Compression Using Three-Dimensional Wavelet Coding

    Xiaoli Tang;William A. Pearlman;James W. Modestino

  • Source coding of the discrete Fourier transform

    W. Pearlman;R. Gray

  • Hyperspectral Image Compression Using Three-Dimensional Wavelet Coding: A Lossy-to-Lossless Solution †

    Xiaoli Tang;William A. Pearlman;James W. Modestino

Frequent Co-Authors

Amir Said
Amir Said Qualcomm (United States)
Zixiang Xiong
Zixiang Xiong Texas A&M University
John W. Woods
John W. Woods Rensselaer Polytechnic Institute
Xiaolin Wu
Xiaolin Wu McMaster University
Robert M. Gray
Robert M. Gray Stanford University
Yehoshua Y. Zeevi
Yehoshua Y. Zeevi Technion – Israel Institute of Technology
xin li
xin li Louisiana State University

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