Digital image noise estimation using DWT coefficients

Varad Pimpalkhute, Rutvik Page, Ashwin Kothari, Kishor M Bhurchandi

Abstract:

Noise type and strength estimation are important
in many image processing applications like denoising, compression, video tracking, etc. There are many existing methods for
estimation of the type of noise and its strength in digital images.
These methods mostly rely on the transform or spatial domain
information of images. We propose a hybrid Discrete Wavelet
Transform (DWT) and edge information removal based algorithm
to estimate the strength of Gaussian noise in digital images. The
wavelet coefficients corresponding to spatial domain edges are
excluded from noise estimate calculation using a Sobel edge
detector. The accuracy of the proposed algorithm is further
increased using polynomial regression. Parseval’s theorem mathematically validates the proposed algorithm. The performance of
the proposed algorithm is evaluated on a standard LIVE image
dataset. Benchmarking results show that the proposed algorithm
outperforms all other state of the art algorithms by a large
margin over a wide range of noise.