Estimating Image Noise Based on Region Segmentation in the Wavelet Domain
Qi Zhang · Jisuanji gongcheng · 2004
A new method is proposed to estimate image noise. The algorithm can improve traditional ones because it allows additional local information of the image (such as the identification of smooth or edge regions), and it recovers the variance of the noise in two steps. First, based on the distribution of wavelet high-frequency coefficients,the smooth regions in an image are extracted and a variance estimate sequence for these regions is yielded. In the second part of the algorithm, the value of the noise variance is determined from this variance estimate sequence. This paper applies the blind noise variance algorithm to some noisy images often employed in computer vision and image processing. Experimental results are provided which indicate that the novel method can provide better result than other traditional ones. These results are useful in image denoising.