Optimized Noise Reduction in Images Applying Artificial Bee Colony Based Technique
Manjula K. A.1, C. Suresh kumar2
1Manjula K. A.*, Research scholar, Research and Development Centre, Bharathiar University, Tamilnadu, India.
2Dr. C. Suresh kumar, Research and Development Centre, Bharathiar University, Tamilnadu, India.

Manuscript received on January 02, 2020. | Revised Manuscript received on January 15, 2020. | Manuscript published on January 30, 2020. | PP: 2555-2557 | Volume-8 Issue-5, January 2020. | Retrieval Number: E6469018520/2020©BEIESP | DOI: 10.35940/ijrte.E6469.018520

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Digital image processing techniques have become inevitable in image related research areas and the major challenge is in collecting good quality images. Usually images suffer from noises and this will affect the accuracy of research findings. Because of this reason, noise removal is a crucial step in image processing tasks. Biologically-inspired soft-computing algorithms, originated by imitating evolution and foraging techniques of insects and animals in nature, have attracted a lot of research interests . This study presents development of a noise reduction technique based on a biologically inspired algorithm – Artificial Bee Colony Algorithm(ABC) – and analyses its optimization capabilities. This study throws light towards the potential of ABC algorithm to work as an effective smoothening filter for images.
Keywords: ABC Algorithm, Noise Reduction, Optimization.
Scope of the Article: Parallel and Distributed Algorithms.