Approximate Stochastic Computing (ASC) for Image Processing Applications


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)


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


File Type





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

Publication Date

01 Oct 2016