@article{MAKHILLJEAS2018131116304,
    title = {Hybrid Algorithm for Image De-Noising},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {13},
    number = {11},
    pages = {4015-4019},
    year = {2018},
    issn = {1816-949x},
    doi = {jeasci.2018.4015.4019},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2018.4015.4019},
    author = {Enas and},
    keywords = {image processing,expansional function,logarithm function,morphology,De-noising,methods},
    abstract = {The search for efficient image de-noising methods still is a valid challenge at the crossing of
functional analysis and statistics. In spite of the sophistication of the recently proposed methods most
algorithms have not yet attained a desirable level of applicability. In this study, a hybrid denoising method is
proposed to find the best possible solutions, so that, PSNR (Peak Signal Noise-to-Ratio) value of the image
after denoising process is optimal. The proposed model is based on morphologic filter which has been
successfully used in noise removal and hybrid with proposed mathematical algorithm which exploits the
potential features of both morphologic filter and mathematical algorithm at the same time their limitations are
overcome. Three types of noise inserted on colored image and then removed by suggested filters to check the
relation between the noise type and noise removing methods. The types of noise amplifier noise (Gaussian
noise), salt and pepper noise, speckle noise. The quality performance of these methods was checked by visual
checking of the resultant images and determining the PSNR value.}
    }