Enhancing Digital Images Using Feed Forward Neural Network
Journal Title: International Journal of Engineering Sciences & Research Technology - Year 30, Vol 3, Issue 7
Abstract
A neural filtering technique is proposed to enhance the digital images when images are contaminated by impulse noise. This filter is obtained by combining nonlinear filter and feed forward neural network with back propagation algorithm. Nonlinear filtering output is converted into one dimensional sequence in four different ways for neural network training. The neural network is trained using three well known images and the network architecture is tuned to optimization. Using this optimized structure, unknown images are tested. Extensive simulation results show that the proposed intelligent filter is superior performance than the other existing neural filters and nonlinear filters in terms of eliminating impulse noise and preserving edges and fine details.
Authors and Affiliations
R. Pushpavalli*
Keywords
Related Articles
- EP ID EP106144
- DOI -
- Views 125
- Downloads 0
REAL TIME INDIAN SIGN LANGUAGE RECOGNITION SYSTEM TO AID DEAFDUMB PEOPLE USING COLOR EDGE DETECTION ALGORITHM
The Sign Language is a method of communication for deaf dumb people. This paper proposes a method that provides a basis for the development of Sign Language Recognition system for one of the south Indian languages...
DYNAMIC PERFORMANCE OF UPFLOW ANAEROBIC SLUDGE BLANKET REACTOR TREATING MUNICIPAL WASTEWATER AT LOW TEMPERATURE
To explore the suitability of simple CSTR model for evaluating the dynamic performance of upflow anaerobic sludge blanket (UASB) reactor treating municipal wastewater at low temperature. The simultaneous dynam...
Equilibrium and Kinetics of Glass Beads and Activated Carbon for Removal of Pb (II), Hg (II), and Cd (II) from Wastewater by Adsorption
The effect of partially replacing granular activated carbon (GAC) by glass beads (GB) in fixed bed for adsorption of Pb(II), Hg(II), and Cd(II) ions onto activated carbon were investigated. Experiments were carrie...
Nonlinear Process Identification using Neural Networks
In industry process control, the model identification of nonlinear systems are always difficult problems. The main aim of this paper is to establish a reliable model for the nonlinear process. In many applications...
A Process Development FOR Extraction of Marker Compound from EMBLICA OFFICINALIS FRUIT
The present study is done to examine and optimize the process of enzyme-assisted extraction of Gallic acid from the dried fruit of Emblica officinalis. The aqueous extraction yielded 12.09% of Gallic acid. A selective...