Image Enhancement using Thermal-visible Fusion for Human Detection

• Main Authors: Ezrinda, Mohd Zaihidee, Kamarul Hawari, Ghazali, Mohd Zuki, Salleh
• Format: Conference or Workshop Item
• Language: English
• Published: IOP Publishing Ltd 2017
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://umpir.ump.edu.my/id/eprint/19856/1/Zaihidee_2017_J._Phys.%253A_Conf._Ser._890_012038.pdf; http://umpir.ump.edu.my/id/eprint/19856/; https://doi.org/10.1088/1742-6596/890/1/012038; https://doi.org/10.1088/1742-6596/890/1/012038
• Institution: Universiti Malaysia Pahang

An increased interest in detecting human beings in video surveillance system has emerged in recent years. Multisensory image fusion deserves more research attention due to the capability to improve the visual interpretability of an image. This study proposed fusion techniques for human detection based on multiscale transform using grayscale visual light and infrared images. The samples for this study were taken from online dataset. Both images captured by the two sensors were decomposed into high and low frequency coefficients using Stationary Wavelet Transform (SWT). Hence, the appropriate fusion rule was used to merge the coefficients and finally, the final fused image was obtained by using inverse SWT. From the qualitative and quantitative results, the proposed method is more superior than the two other methods in terms of enhancement of the target region and preservation of details information of the image.