  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.
