Analysis and Extension of the Ponomarenko et al. Method, Estimating a Noise Curve from a Single Image

Abstract

In the article "An Automatic Approach to Lossy Compression of AVIRIS Images" N.N. Ponomarenko et al. propose a new method to specifically compress AVIRIS images. As part of the compression algorithm, a noise estimation is performed with a proposed new algorithm based on the computation of the variance of overlapping 8x8 blocks. The noise is estimated on the high-frequency orthonormal DCT-II coefficients of the blocks. To avoid the effect of edges and textures, the blocks are sorted according to their energy measured on a set of low-frequency coefficients. The final noise estimation is obtained by computing the median of the variances measured on the high-frequency part of the spectrum of the blocks using only those whose energy (measured on the low-frequencies) is low. A small percentile of the total set of blocks (typically the 0.5%) is used to select those blocks with the lower energy at the low-frequencies. Although the method measures uniform Gaussian noise, it can be easily adapted to deal with signal-dependent noise, which is realistic with the Poisson noise model obtained by a CCD device in a digital camera.