(untitled) (International Journal of Engineering and Computer Science, 2017)
Most of the image processing techniques such as edge detection, segmentation, object tracking, pattern recognition etc. do not perform well in the occurrence of noise. Thus, image restoration as a preprocessing step is performed before applying the image to any of the beyond mentioned techniques. This dissertation work presents an Decision based unsymmetric trimmed median filter algorithms for the removal of impulse noise has been proposed with color images rather than gray scale images by separation red- green- blue plane of color image. This proposed algorithm shows better results than the Standard Median Filter (MF), Decision Based Algorithm (DBA),Adaptive Median Filter(AMF) , Hybrid Filter Based Algorithm (HMF), and Trimmed Median Filter (TMF). The show of the system is analyzed in terms of Mean square error (MSE), Peak signal to noise ratio (PSNR) image enhancement factor (IEF) and time required for executing the algorithms for different noise densities. Simulation results shows that proposed algorithm outperforms the existing algorithms even at high noise densities for color images. Many experiments are conducted to validate efficiency of the proposed algorithm.