A Multiple Image-Based Noise Level Estimation Algorithm

In this letter, a novel multiple image-based Gaussian noise level estimation (NLE) algorithm for natural images by jointly exploiting the noise level-aware feature extraction and the local means (LM) estimation techniques was proposed. We employed some efficient and powerful noise level-aware featur...

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Bibliographic Details
Published in:IEEE signal processing letters 2017-11, Vol.24 (11), p.1701-1705
Main Authors: Xu, Shaoping, Zeng, Xiaoxia, Jiang, Yinnan, Tang, Yiling
Format: Article
Language:English
Subjects:
Computational efficiency
Estimation
Feature extraction
image denoising
Image resolution
local means estimation
multiple image-based approach
Noise level
noise level estimation (NLE)
noise level-aware feature vector
Noise measurement
Signal processing algorithms
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Summary:In this letter, a novel multiple image-based Gaussian noise level estimation (NLE) algorithm for natural images by jointly exploiting the noise level-aware feature extraction and the local means (LM) estimation techniques was proposed. We employed some efficient and powerful noise level-aware features in the form of a feature vector to characterize the noise levels across image contents. Based on this, we adopted LM estimation scheme to estimate the noise level for an image to be estimated by comparing multiple images of similar noise levels in a preconstructed sample database. We had verified the accuracy and efficiency of the proposed NLE algorithm on a large of images from several benchmark databases. Compared with the competing NLE algorithms, our algorithm is superior to them for noise level estimation in terms of both estimation accuracy and execution time.
ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2017.2755687