Research on Image Enhancement Algorithm for Forest Fire under Low Illumination

Addressing issues such as low contrast, blurred flames and smoke, as well as forest fog interference in low-light forest fire images, an image enhancement approach based on an optimized MSRCP algorithm is proposed. This method first converts the original image from the RGB color space to the HSV color space, and applies a weighted MSR operation to the Value (V) component. Secondly, a piecewise Gamma correction is employed to adjust the brightness of the MSR-processed V component. Finally, the fused image is remapped back to the RGB color domain, and the CLAHE algorithm is utilized to further enhance the image contrast. Experimental results demonstrate that the improved algorithm effectively enhances the clarity of flames, smoke, and objects obscured by forest fog. Furthermore, it mitigates the common issues of overexposure and underexposure encountered in MSRCP processing. Compared to the MSRCP algorithm, the improved algorithm achieves enhancements of 2.19%, 22.44%, and 2.06% respectively in the metrics of average gradient, edge strength, and information entropy.