Optimal Architectures for Multidimensional Transforms

Abstract

Multidimensional transforms have widespread applications in computer vision, pattern analysis and image processing. The only existing optimal architecture for computing multidimensional DFT on data of size n = Nd requires very large rotator units of area O(n^2) and pipeline-time O(log n). In this paper we propose a family of optimal architectures with areatime trade-offs for computing multidimensional transforms. The large rotator unit is replaced by a combination of a small rotator unit, a transpose unit and a block rotator unit. The combination has an area of O(N^(d+2a)) and a pipeline time of O(N^(d/2-a)log n), for 0 < a < d/2. We apply this scheme to design optimal architectures for two-dimensional DFT, DHT and DCT. The computation is made efficient by mapping each of the one-dimensional transforms involved into two dimensions.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1988
Accession Number
AD1007036

Entities

People

  • Chaitali Chakrabarti
  • Joseph Ja'ja'

Organizations

  • University of Maryland

Tags

DTIC Thesaurus Topics

  • Computations
  • Computer Vision
  • Computers
  • Data Processing
  • Identification
  • Image Processing
  • Image Recognition
  • Information Processing
  • Mathematics
  • Pipelines
  • Recognition
  • Two Dimensional

Fields of Study

  • Engineering

Readers

  • Approximation Theory.
  • Distributed Systems and Data Platform Development
  • Trauma Surgery or Emergency Medicine.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms