Optimization of Underwater Image Objects with Noise Analysis Using a Gaussian Filter Selected Algorithm

DOI

10.2991/aisr.k.200424.040How to use a DOI?

Keywords

filters block, variable bitspace adder, under water image

Abstract

Different types of images when testing will give different results. Between still images and moving images requires speed and accuracy in the computation process. This is due to the availability of time in processing which tends to narrow at any time along with environmental changes. Retesting of processors that have been built through previous research requires the selection of new image data and processes. The selection of the new image refers to a different image and has never been used before. Next, for the new process by applying Gaussian filtering selection (filters block). The results of the first stage in testing of some images obtained that the ‘bit space adder/sub’ accuracy value and using filters block for underwater objects image data test was 90.91% in the first cycle. However, when compared to the architecture of least significant bit only obtained an accuracy of 0.01% so that there is a very significant difference in accuracy, which is equal to 90.90%. This result will improve if added using a filter block, the accuracy value rises to 95.75%.

Copyright

© 2020, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Sukemi
AU  - Yogi TIARA PRATAMA
PY  - 2020
DA  - 2020/05/06
TI  - Optimization of Underwater Image Objects with Noise Analysis Using a Gaussian Filter Selected Algorithm
BT  - Proceedings of the Sriwijaya International Conference on Information Technology and Its Applications (SICONIAN 2019)
PB  - Atlantis Press
SP  - 269
EP  - 275
SN  - 1951-6851
UR  - https://doi.org/10.2991/aisr.k.200424.040
DO  - 10.2991/aisr.k.200424.040
ID  - 2020
ER  -