An Adaptive Exposure Fusion Method Using Fuzzy Logic and Multivariate Normal Conditional Random Fields

• Published in: Sensors (Basel, Switzerland) Vol. 19; no. 21; p. 4743
• Main Authors: Lin, Yu-Hsiu, Hua, Kai-Lung, Lu, Hsin-Han, Sun, Wei-Lun, Chen, Yung-Yao
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 31.10.2019; MDPI
• Subjects: Autonomous cars; Blending; coarse-to-fine tuning; Conditional random fields; Decomposition; detail manipulation; Exposure; exposure fusion; Fuzzy logic; Image enhancement; intelligent vision sensing; Medical imaging; Methods; Multivariate analysis; Noise
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s19214743

High dynamic range (HDR) has wide applications involving intelligent vision sensing which includes enhanced electronic imaging, smart surveillance, self-driving cars, intelligent medical diagnosis, etc. Exposure fusion is an essential HDR technique which fuses different exposures of the same scene into an HDR-like image. However, determining the appropriate fusion weights is difficult because each differently exposed image only contains a subset of the scene’s details. When blending, the problem of local color inconsistency is more challenging; thus, it often requires manual tuning to avoid image artifacts. To address this problem, we present an adaptive coarse-to-fine searching approach to find the optimal fusion weights. In the coarse-tuning stage, fuzzy logic is used to efficiently decide the initial weights. In the fine-tuning stage, the multivariate normal conditional random field model is used to adjust the fuzzy-based initial weights which allows us to consider both intra- and inter-image information in the data. Moreover, a multiscale enhanced fusion scheme is proposed to blend input images when maintaining the details in each scale-level. The proposed fuzzy-based MNCRF (Multivariate Normal Conditional Random Fields) fusion method provided a smoother blending result and a more natural look. Meanwhile, the details in the highlighted and dark regions were preserved simultaneously. The experimental results demonstrated that our work outperformed the state-of-the-art methods not only in several objective quality measures but also in a user study analysis.