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Digital Image Enhancement using Histogram equalization (HE) technique for Grey Scale Images

Priya Surana, Rakesh Kumar

Abstract


ABSTRACT

Digital images are playing a crucial role in distinctive programs regions inclusive of video surveillance, Radar, medical images and satellite tv for satellite imaging. The major concerns with the received images are their noise and low comparison. The contrast of the photo comes to a decision the quality of the photo. evaluation enhancement is used to carry out the adjustment on darkness or lightness of the photograph. Histogram equalization (HE) is a simple and broadly used image evaluation enhancement approach. Histogram equalization stretches the histogram across the entire spectrum of pixels (0 – 255).  Histogram equalization is one of the operations that can be applied to obtain new images based on histogram specification or modification. It is a contrast enhancement technique with the objective to obtain a new enhanced image with a uniform histogram.

 

Keywords: Digital Image Processing, Histogram Equalization, MATLAB, Contrast Enhancement, Condition monitoring, fuzzy logic, Neural networks.

CitCite this Article: Priya Surana, Rakesh Kumar. Digital Image Enhancement using Histogram equalization (HE) technique for Grey Scale Images. International Journal of VLSI design and technology. 2019; 5(2): 39–45p


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References


Cicero F. F. Costa Filho, Marly G. F. Costa, Joao E. Chaves Filho, and Alvaro L. M. de Oliveira, “Using a random restart hill-climbing algorithm to reduce component assembly time in printed circuit boards,” IEEE International conference on Industrial Technology may 2010, Vina del Mar, Chile.

E. K. Burke, P. I. Cowling, R. Keuthen, “Effective heuristic and metaheuristic approaches to optimize component placement in printed circuit board assembly”, Proceedings of the IEEE Conference on Evolutionary Computation, ICEC, v 1, pp 301-308, 2000, La Jolla, CA, USA, USA.

E. K. Burke, P.I. Cowling and R. Keuthen, “New Models and Heuristics for Component Placement in Printed Circuit Board Assembly”. Proceedings of the 1999 International Conference on Information Intelligence and Systems, pp.133-140, 1999.

W. Ho and P. Ji. “A Hybrid Genetic Algorithm for Component Sequencing and Feeder Arrangement”. Journal of Intelligent Algorithm, 15, pp.307- 315, 2004.

W. Lee, S. Lee, B. Lee and Y. Lee. “A Genetic Optimization Approach to Operation of a Multi Head Surface Machine”. IEICE Trans. Fundamentals, E83-A (9), pp. 1748-1756, 2000.

C. H. Craveiro, “Otimização do Posicionamento e da Montagem Automática de Componentes Eletrônicos Através de um Algoritmo Genético”. Dissertação de mestrado, orientada por Amit Bhaya, COPPE, Universidade Federal do Rio de Janeiro, 2005.

E. Carvalho. “Uso de Algoritmos Meméticos na Utilização de Seqüências de Montagem de Máquinas SMD”. Dissertação de mestrado orientada por J. E. Chaves Filho, Universidade Federal do Amazonas, 2007.

C. S. Rabak and J. S. Sichman, “Using A.Teams to optimize automatic insertion of electronic components”, Advanced Engineering Informatics, 17(2), pp. 95-106, 2003.




DOI: https://doi.org/10.37628/jvdt.v5i2.1136

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