期刊
APPLIED SCIENCES-BASEL
卷 13, 期 18, 页码 -出版社
MDPI
DOI: 10.3390/app131810230
关键词
brightness enhancement; image fusion; image processing; Laplacian pyramid
This paper proposes a low-brightness image enhancement algorithm based on multi-scale fusion. By using brightness transformation and illumination estimation techniques, advantageous features are extracted and images are fused to improve image quality. Experimental results demonstrate that the proposed method has better enhancement effect.
Images captured in low-brightness environments typically have low brightness, low contrast, and high noise levels, which significantly affect the overall image quality. To improve the image quality, a low-brightness image enhancement algorithm based on multi-scale fusion is proposed. First, a novel brightness transformation function is used for the generation of two images with different brightnesses. Then, the illumination estimation technique is used to construct a weight matrix, which facilitates the extraction of advantageous features from each image. Finally, the enhanced image is obtained by the fusion of two images using the weight matrix and the pyramid reconstruction algorithm. The proposed method has a better enhancement effect as shown by the experimental results. Compared to other image enhancement algorithms, it has lower evaluation values in the natural image quality evaluator (NIQE) and lightness order error (LOE) indices. The lowest average NIQE value of the proposed algorithm in each dataset is 2.836. This further demonstrates its superior performance.
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