Image fusion based on object region detection and Non-Subsampled Contourlet Transform
| Autor: | Baolong Guo, Dalong Shan, Fanjie Meng, Ruixia Shi, Miao Song |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Fusion
Image fusion General Computer Science Computer science business.industry Region detection 020206 networking & telecommunications Pattern recognition 02 engineering and technology Object (computer science) Contourlet Image (mathematics) Control and Systems Engineering 0202 electrical engineering electronic engineering information engineering Fusion rules 020201 artificial intelligence & image processing Computer vision Saliency map Artificial intelligence Electrical and Electronic Engineering business |
| Zdroj: | Computers & Electrical Engineering. 62:375-383 |
| ISSN: | 0045-7906 |
| DOI: | 10.1016/j.compeleceng.2016.09.019 |
| Popis: | This paper presents a new fusion algorithm for infrared (IR) and visible light (ViS) images by combining object region detection with the Non-Subsampled Contourlet Transform (NSCT). First, the saliency map for the IR image is acquired with saliency detection. Second, the object region in the IR image is extracted by introducing a free regions removal method. Third, source images are decomposed via NSCT and different fusion rules for low frequency sub-bands and high frequency sub-bands are employed. Then, the primary fused image is generated by the inverse NSCT. Finally, integrating the primary fused image with the object region, the final fused image is obtained. By conducting experiments, we compare our method to others using several metrics and results show that the proposed method can improve the quality of the fused image. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect