- published
- 2013-07-23
- reference
- Miguel Colom, and Antoni Buades, Analysis and Extension of the Ponomarenko et al. Method, Estimating a Noise Curve from a Single Image, Image Processing On Line, 3 (2013), pp. 173–197. https://doi.org/10.5201/ipol.2013.45
Communicated by Bartomeu Coll
Demo edited by Miguel Colom
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.
Download
- full text manuscript: PDF low-res. (689K) PDF (9.8M) [?]
- source code: ZIP
History
- 2013-07-23: original publication - source code
- 2014-02-27: bugfix in file subscale/algo.cpp at the algorithm(...) function.
- Note from the editor: the manuscript of the article was modified on 2022-01-01 to include information about its editors. The original version of the manuscript is available here.