Transform and statistical parameter-based image noise level prediction

Noise level estimation in an image is important and useful in many image processing algorithms such as image denoising, image segmentation, and image compression. Accurately estimating the noise level without prior knowledge of the image is the major challenge of today’s research. We present an improved patch-based fast noise level estimation using DCT and standard deviation method for fast and reliable noise level estimation and the result is compared with the available state-of-art methods. Experimental result shows the proposed method provides greater accuracy, the stability and also the proposed method is an average of six times faster than that of the state- of – art methods for noise level estimation.