Optimum non linear binary image restoration through linear grey-scale operations

Non-linear image processing operators give excellent results in a number of image processing tasks such as restoration and object recognition. However they are frequently excluded from use in solutions because the system designer does not wish to introduce additional hardware or algorithms and because their design can appear to be ad hoc. In practice the median filter is often used though it is rarely optimal. This paper explains how various non-linear image processing operators may be implemented on a basic linear image processing system using only convolution and thresholding operations. The paper is aimed at image processing system developers wishing to include some non-linear processing operators without introducing additional system capabilities such as extra hardware components or software toolboxes. It may also be of benefit to the interested reader wishing to learn more about non-linear operators and alternative methods of design and implementation. The non-linear tools include various components of mathematical morphology, median and weighted median operators and various order statistic filters. As well as describing novel algorithms for implementation within a linear system the paper also explains how the optimum filter parameters may be estimated for a given image processing task. This novel approach is based on the weight monotonic property and is a direct rather than iterated method

A Digit-Serial Architecture for Gray-Scale Morphological Filtering

We present a digit-serial architecture for gray-scale morphological operations which operates on radix-2 redundant numbers. We present new implementations of a redundant number adder and maximum unit used in the morphological dilation unit. These new designs have areas comparable to 2's complement implementations, but have significantly smaller latencies. 1. INTRODUCTION Morphological operations are widely used in image processing applications for feature extraction and machine vision applications [1]. The basic morphological operations are dilation, erosion, opening, and closing. Complex operations such as skeletonization and feature extraction utilize these basic operations [2]. Morphological operations can be defined in the binary domain as well as in the gray-scale domain. Morphological operations in the gray-scale domain are significantly more complex than those in the binary domain. The operations in the gray-scale domain require additions and subtractions followed by minimum ..