Approximate Arithmetic for Low-Power Image Median Filtering

Abstract

In applications related to human senses, such as audio and image processing, computations with limited precision are acceptable. In these areas, a digital system can be implemented using approximate computing that works with sufficient precision. In this paper, we present a method to design 2-bit approximate magnitude comparators that are effectively low cost in terms of power, area and speed. We build larger comparators with adjustable error characteristics. Compared to precise one, our approximate comparators can save power and area up to 7-46 % and 10-50 %, respectively. The structures of our comparators and their error characteristics are presented in this paper. We use these comparators to design different approximate image median filters in order to remove salt and pepper noise. Simulation results show that the output quality of these filters is very similar to that of the precise ones so that the degradation is not noticeable. The approximate filters save up to 30 % of power and area while working 18 % faster than the precise ones.

Area Efficient Parallel Median Filter Using Approximate Comparator and Faithful Adder

“…Median filter performs sorting on a set of inputs in a processing window to replace the corrupted centre pixel with the median value. Sorting algorithms employed in median filter design fall into three main categories viz., systolic array, network‐based sorting, and radix method or threshold decomposition filter [22]. Parallel operation is possible with sorting based algorithm to design high‐speed median filter architecture.…”

“…Monajati et al [22] proposed a novel approach for approximate PMF (APMF) with error‐tolerant comparators. n ‐bit CS units with a combination of 2‐bit approximate and exact comparators are proposed and implemented in APMF.…”

“…Systolic array‐based pipelined median filters are proposed in [20, 21]. Approaches to the design of approximate comparators targeting low‐power and area‐efficient median filters are proposed in [22, 23]. A high‐speed area‐efficient median filter using a novel sorting algorithm is proposed by Vasanth et al [24].…”

Approximate Circuits in Low-Power Image and Video Processing: The Approximate Median Filter

“…It has to be noticed that these approximation strategies differ from the approximate median filters proposed in the literature because: paper [26] utilizes approximate transistorlevel circuits to implement the comparators (our comparators are always exact) and papers [3], [27] do not initialize CGP with existing median implementations, but rather evolve approximate circuits form scratch using insufficient resources.…”

Energy-efficient Gaussian filter for image processing using approximate adder circuits

“…These filtering operations generally demand an intensive use of arithmetic operations, thus increasing the energy consumption in the system. Gaussian filter (GF) is a convolution operator which is used to blur images and to remove noise [5]. In this work, we use integer valued 3x3 and 5x5 convolution kernels, whose hardware convolution implementations are composed of a tree of shift and addition/subtraction operations.…”