MMApr 24, 2019

A Noise-aware Enhancement Method for Underexposed Images

arXiv:1904.10961v1
Originality Synthesis-oriented
AI Analysis

This work addresses image quality issues for photographers and imaging applications, but it is incremental as it builds on existing contrast enhancement methods.

The paper tackles the problem of enhancing underexposed images by addressing over-enhancement in bright regions and noise amplification in dark regions, achieving improved contrast without noise amplification even in strong noise environments.

A novel method of contrast enhancement is proposed for underexposed images, in which heavy noise is hidden. Under low light conditions, images taken by digital cameras have low contrast in dark or bright regions. This is due to a limited dynamic range that imaging sensors have. For these reasons, various contrast enhancement methods have been proposed so far. These methods, however, have two problems: (1) The loss of details in bright regions due to over-enhancement of contrast. (2) The noise is amplified in dark regions because conventional enhancement methods do not consider noise included in images. The proposed method aims to overcome these problems. In the proposed method, a shadow-up function is applied to adaptive gamma correction with weighting distribution, and a denoising filter is also used to avoid noise being amplified in dark regions. As a result, the proposed method allows us not only to enhance contrast of dark regions, but also to avoid amplifying noise, even under strong noise environments.

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