TUTCRIS - Tampereen teknillinen yliopisto


Blind estimation of white Gaussian noise variance in highly textured images



OtsikkoElectronic Imaging
AlaotsikkoImage Processing: Algorithms and Systems XVI
KustantajaSociety for Imaging Science and Technology
DOI - pysyväislinkit
TilaJulkaistu - 2018
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaIS&T International Symposium on Electronic Imaging -
Kesto: 28 tammikuuta 20182 helmikuuta 2018


ISSN (elektroninen)2470-1173


ConferenceIS&T International Symposium on Electronic Imaging


In the paper, a new method of blind estimation of noise variance in a single highly textured image is proposed. An input image is divided into 8x8 blocks and discrete cosine transform (DCT) is performed for each block. A part of 64 DCT coefficients with lowest energy calculated through all blocks is selected for further analysis. For the DCT coefficients, a robust estimate of noise variance is calculated. Corresponding to the obtained estimate, a part of blocks having very large values of local variance calculated only for the selected DCT coefficients are excluded from the further analysis. These two steps (estimation of noise variance and exclusion of blocks) are iteratively repeated three times. For the verification of the proposed method, a new noise-free test image database TAMPERE17 consisting of many highly textured images is designed. It is shown for this database and different values of noise variance from the set {25, 49, 100, 225}, that the proposed method provides approximately two times lower estimation root mean square error than other methods.