Statistical Features Based Noise Type Identification
Keywords: machine learning, digital image processing, Noise Type Identification
Abstract
In this paper, a new technique for automatically identifying the type of noise in digital images has been proposed. Our statistical features based noise Type identification scheme uses machine learning to distinguish different types of noises. Local features of 3x3 window are used to train the machine learning based classifier. Two types of noise (salt & peppers and random-valued) is catered for in this paper. Experiments show that the proposed technique gives promising results and can be enhanced to be a generic noise identification system for every type of noise.
Más información
Título según WOS: | Statistical Features Based Noise Type Identification |
Título según SCOPUS: | Statistical features based noise type identification |
Título de la Revista: | BIO-INSPIRED SYSTEMS AND APPLICATIONS: FROM ROBOTICS TO AMBIENT INTELLIGENCE, PT II |
Volumen: | 8857 |
Editorial: | SPRINGER INTERNATIONAL PUBLISHING AG |
Fecha de publicación: | 2014 |
Página de inicio: | 231 |
Página final: | 241 |
Idioma: | English |
Notas: | ISI, SCOPUS |