A Multi-Scale Fusion-Based Method for Ultra-Low-Light Agricultural Image Enhancement

Fruits, vegetables, and medicinal herbs are often processed in enclosed spaces with low light.These conditions create uneven lighting, produce dark images, distort colors, and increase noise, all of which make remote monitoring difficult and reduce product quality.This paper uses tobacco leaf curing as an example to introduce a Multi-Scale Fusion-Based Image Enhancement (MSFIE) technique designed to address these problems.Histogram equalization, a CLAHE module, an enhanced dualgamma correction, and a multi-scale fusion framework are all included in the technique.When combined, these elements improve overall contrast and sharpness, lessen local overexposure, and brighten dark areas.The primary and secondary leaf vein structures are further made clearer by a detail enhancement technique.Experiments on 150 ultra-low-light images demonstrate that MSFIE improves visual quality, brightness uniformity, detail preservation, and color accuracy.Quantitatively, it achieves consistent gains in Shannon entropy, peak signal-to-noise ratio, laplacian-based sharpness, local contrast, frequency-domain sharpness, luminance skewness, and information entropy.