Blind Content Independent Noise Estimation for Multimedia Applications
Pranav Sodhani, Akshat Bordia, Kannan Karthik · Procedia Computer Science · 2015
This paper presents a completely blind or no-reference metric for estimation of perceived noise in images. This novel metric dubbed CINEMA (Content Independent Noise Estimation for Multimedia Applications) is completely content unaware and aligns well with human perception. An HOG-based model is employed for selection of weak textured patches and a wavelet decomposition strategy is used for detecting and quantifying noise. Experimental results on the LIVE database show that CINEMA achieves consistently good performance for different noise levels as compared to many of the existing Full Reference and No Reference Image Quality Assessment (IQA) metrics. We further show how CINEMA can be used to obtain an estimate (σ̂) of the noise standard deviation (σ) with high accuracy. A MATLAB implementation of the model is available at https://sites.google.com/site/blindiqa/cinema.