Nonlinear Digital Filters pp 345-387 | Cite as

# Algorithms and Architectures

## Abstract

One of the main problems in linear as well in the nonlinear image processing is the computational complexity and the execution speed of the image processing routines, especially for applications where real-time image processing is required. This problem mainly results from the amount of the data to be processed (e.g., 256K bytes for a single 512×512 8 bit image) as well as from the number of operations required per output pixel. Such operations are usually comparisons, additions, multiplications, and nonlinear function evaluations. Usually the number of operations required per output pixel is not very high. However, if this number is multiplied by the output image size (in pixels), the total amount of computations required is tremendous. Therefore, even simple nonlinear filters (e.g., median filters, erosion, dilation), which require only comparisons, are relatively slow for fast image processing applications. There are two solutions to the requirement for an increase of the speed of image processing routines. The first one is to construct fast algorithms for linear and nonlinear image processing. These algorithms can be relatively fast on general purpose computers for fast nonreal-time digital image processing. If real-time processing is a must, the only solution is to build image processors, whose architecture is optimized for image processing applications. If the performance of such image processors is not adequate, parallel image processing is the solution.

## Keywords

Median Filter Finite Impulse Response Digital Filter Systolic Array Finite Impulse Response Filter## Preview

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