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.
Recommended citation: Varad Pimpalkhute, Rutvik Page, Ashwin Kothari, Kishor Bhurchandi and Vipin Kamble, "Digital Image Noise Estimation Using DWT Coefficients," in IEEE Transactions on Image Processing, vol. 30, pp. 1962-1972, 2021, doi:10.1109/TIP.2021.3049961.