Statistical Features Based Noise Type Identification

Masood, S; Soto, I.; Hussain A.; Jaffar, MA

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: LEARNING AND INTELLIGENT OPTIMIZATION, LION 15
Volumen: 8857
Editorial: SPRINGER INTERNATIONAL PUBLISHING AG
Fecha de publicación: 2014
Página de inicio: 231
Página final: 241
Idioma: English
Notas: ISI, SCOPUS