New image processing pipelines for membrane detection

Rajeswari Raju, Tomas Henrique Maul, Andrzej Bargiela

Abstract


In this paper, we report an interesting observation pertaining to new image processing pipeline for membrane detection suggested by optimization experiments. Denoising is usually performed in order to minimize the detrimental effects that noise has on the subsequent stages of an algorithm. Thus Denoising is typically carried out as an early pre-processing stage before other core functions are applied. In the context of optimizing image processing chains for membrane detection, we gathered statistics of processing chains which exhibited an average F1 score larger than 90%, and observed that not one was found to use a Denoising function as its 1st step in the processing chain. On the contrary, the optimization process tended to choose Denoising as a middle processing component, and generally selected image enhancement as an earlier component. We conclude, that at least in the context of this membrane detection problem, it is better to enhance information (enhancement) before cleaning it (filtering).

 

 

Keyword: membrane detection; denoising; segmentation; image processing; optimization.

 

 


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DOI: https://doi.org/10.12792/jiiae.3.15

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