Image Processing Pipeline Based on Coupled Oscillator Models

For decades, researchers have been developing algorithms for image processing pipelines. Image Processing Pipelines (IPPs) are algorithmic constructions built to iteratively modify an input image into a series of abstractions for the purposes of decoding its contents into a higher level representation. There have been many proposed IPPs, varying in both physical construction, and in algorithmic paradigm, but by and large these propositions have been based in Boolean computation and arithmetic. Studies and trends have shown that Boolean computers are hitting a theoretical ceiling on their performance in terms of transistor size, energy consumption/heat dissipation, clock rates, and by extension computational time. Due to these issues, researchers have proposed using non-Boolean approaches, where possible, for various computations in common algorithms. One of the emerging technologies in the field of non-Boolean computation has been the use of coupled oscillators. A proposed use of coupled oscillators is for pattern matching, which can also be interpreted as a high-dimensional distance measurement. Using an approach based on the use of coupled oscillators as a basic computational primitive, this work aims to utilize the benefits gained from this new computational paradigm to gain performance in terms of both speed and power with respect to IPPs, without decreasing the accuracy of their algorithms.

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