Flame temperature estimation from light field image processing

We propose a novel flame temperature estimation method based on a flame light field sectioned imaging model of complex temperature distribution in different media. The proposed method relies on multi-pixel reconstruction to improve the resolution of sub-aperture images. In addition, the wavelet transform denoises the flame refocused image, and then the Lucy–Richardson algorithm deconvolves the image. The temperature estimation accuracy using the proposed method is higher than that reported in a previous work, with a larger temperature estimation range from 1250 K to 1800 K. Moreover, we found that deconvolution plays an important role in determining the temperature estimation accuracy.