关键词: 低对比度, 图像增强, 双边滤波器, 图像分割, CV模型

Abstract: For the contrast between fire and background is not obvious, it is hard to extract the low contrast fire. So this paper proposes a fire enhancement and segmentation algorithm based on Retinex and CV (Chan-Vese) model to solve it. Firstly, this paper constructs a color-bilateral filter based on Retinex in the YCbCr color space, and designs a contrast adjustment function to adjust the intensity of each pixel according to the relation of Cr and Cb, which highlights the bright and colorful fire in the image. Secondly, this paper gets the candidate fire area by combining difference frames and color space model, sets the initial contour curve of the CV model according to the center in the area, and obtains the fire area by the further segmentation. The experimental results show that the proposed algorithm can not only extract the low contrast fire in simple and complex background, but also keep the irregular target edge complete, the classification error rate is lower obviously than the existing algorithms. The proposed algorithm is proven to be advanced and effective.

Key words: low contrast, image enhancement, bilateral filter, image segmentation, CV model