Approximate Stochastic Computing (ASC) for Image Processing Applications

Abstract

SC (stochastic computation) has been found to be very advantageous in image processing applications because of its lower area consumption and low-power operation. However, one of the major issues with the SC is its long run-Time requirement for accurate results. In this paper, a new technique called the approximate stochastic computing (ASC) approach called the approximate stochastic computing (ASC) focusing on image processing applications is proposed to reduce the computation time of a SC by a factor of 16 at a trade-off of an error percentage of 3.13% in the absolute stochastic value ([0, 1)) computed. The proposed technique considers only the first four MSBs of the image pixel value for SC, which introduce a maximum error of 6.25% in the stochastic output. Attempts have been made to reduce this error to 3.13% by linearly increasing the clock cycles from 16 to 17 rather than exponentially (ex: 32, 64, 128,256...). Experimental results from SC edge detection circuit indicate that this technique is a promising approach for efficient approximate image processing.

Meeting Name

International SoC Design Conference: ISOCC (2016: Oct. 23-26, Jeju, South Korea)

Department(s)

Electrical and Computer Engineering

Keywords and Phrases

Economic and Social Effects; Edge Detection; Errors; Stochastic Systems; Computation Time; Detection Circuits; Image Pixel Value; Image Processing Applications; Low-Power Operation; Stochastic Computations; Stochastic Computing; Stochastic Values; Image Processing

International Standard Book Number (ISBN)

978-1509032198; 978-1509032204

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2016 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Oct 2016

Link to Full Text

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