RRAM Crossbar-Based In-Memory Computation of Anisotropic Filters for Image Preprocessingloa

Fakhreddine Zayer, Baker Mohammad, Hani Saleh, Gabriele Gianini

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Anisotropic-diffusion is a commonly used signal preprocessing technique that allows extracting meaningful local characteristics from a signal, such as edges in an image and can be used to support higher-level processing tasks, such as shape detection. This paper presents a fully scalable CMOS-RRAM architecture of an edge-aware-anisotropic filtering algorithm aimed at computer vision applications. The CMOS circuitry controls the scale-space image data to perform pseudo-parallel in-memory computing and nonlinear processing through RRAM crossbar. The arithmetic operations for in-memory computation of brightness gradients are efficiently accumulated to produce the enhanced image in several iterations. The proposed architecture uses single RRAM as a computing and storage element to perform both arithmetic operations and accumulations. Thanks to the in-memory computation, memory accesses and arithmetic operations are reduced by 64% and 92%, respectively, compared to traditional digital implementations. This, in turn, results in a potential reduction of power and area costs of about 75% and 85%, respectively. The processing time is also reduced by 67%.

Original languageBritish English
Article number9122505
Pages (from-to)127569-127580
Number of pages12
JournalIEEE Access
Volume8
DOIs
StatePublished - 2020

Keywords

  • anisotropic diffusion
  • image enhancement
  • in memory computing
  • RRAM crossbar
  • Scale-space image

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