The light field camera has emerged as an optical flame temperature detection device owing to the refocusing feature. Combining this feature with the deconvolution algorithm, a three-dimensional flame temperature distribution can be reconstructed. However, the accuracy of reconstructing the flame temperature is limited by the actual image position. Based on the established flame and light field camera model, the proposed Lucy-Richardson and Nearest Neighbor Filtering joint deconvolution algorithm is applied to sectioned temperature reconstruction. Thus, the effects of image position using light field camera on temperature reconstruction are verified. The relative error of flame temperature reconstruction is less than 10%, if the flame is imaged in the middle of the light field image. However, if the flame is imaged at the image edge, the edge distortion and defocused state of the camera increase the relative error to less than 11% and 14%, respectively. The effects of image positions are not too significant for temperature reconstruction using light field camera.

由于重新聚焦特征，光场相机已经成为光学火焰温度检测装置。将此特征与反卷积算法相结合，可以重建三维火焰温度分布。但是，重建火焰温度的精度受到实际图像位置的限制。在已建立的火焰和光场相机模型的基础上，将所提出的露西-理查森和最近邻滤波联合反卷积算法应用于分段温度重构。因此，验证了使用光场相机的图像位置对温度重建的影响。如果火焰在光场图像的中间成像，则火焰温度重建的相对误差小于10％。但是，如果火焰在图像边缘成像，相机的边缘变形和散焦状态会使相对误差分别小于11％和14％。对于使用光场相机进行温度重建，图像位置的影响不太明显。