Title
A fusion-based enhancing method for weakly illuminated images.
Abstract
We propose a straightforward and efficient fusion-based method for enhancing weakly illumination images that uses several mature image processing techniques. First, we employ an illumination estimating algorithm based on morphological closing to decompose an observed image into a reflectance image and an illumination image. We then derive two inputs that represent luminance-improved and contrast-enhanced versions of the first decomposed illumination using the sigmoid function and adaptive histogram equalization. Designing two weights based on these inputs, we produce an adjusted illumination by fusing the derived inputs with the corresponding weights in a multi-scale fashion. Through a proper weighting and fusion strategy, we blend the advantages of different techniques to produce the adjusted illumination. The final enhanced image is obtained by compensating the adjusted illumination back to the reflectance. Through this synthesis, the enhanced image represents a trade-off among detail enhancement, local contrast improvement and preserving the natural feel of the image. In the proposed fusion-based framework, images under different weak illumination conditions such as backlighting, non-uniform illumination and nighttime can be enhanced. HighlightsA fusion-based method for enhancing various weakly illuminated images is proposed.The proposed method requires only one input to obtain the enhanced image.Different mature image processing techniques can be blended in our framework.Our method has an efficient computation time for practical applications.
Year
DOI
Venue
2016
10.1016/j.sigpro.2016.05.031
Signal Processing
Keywords
Field
DocType
Image enhancement,Multi-scale fusion,Weakly illumination,Weights,Illumination adjustment
Computer vision,Weighting,Closing (morphology),Image processing,Fusion,Adaptive histogram equalization,Backlight,Artificial intelligence,Mathematics,Computation,Sigmoid function
Journal
Volume
Issue
ISSN
129
C
0165-1684
Citations 
PageRank 
References 
64
1.59
42
Authors
6
Name
Order
Citations
PageRank
Xueyang Fu135429.09
Delu Zeng216411.46
Yue Huang331729.82
Yinghao Liao42016.56
Xinghao Ding559152.95
John Paisley6100355.70