改进直方图匹配和自适应均衡的水下图像增强

Underwater Image Enhancement Based on Improved Histogram Matching and Adaptive Equalization

  • 摘要: 为了更有效地改善水下图像的颜色,进一步提升图像的对比度和清晰度,提出改进直方图匹配和自适应均衡的水下图像增强方法。以像素均值最大的通道图像的直方图作为基准,对各通道图像分别进行直方图匹配,校正水下图像的颜色偏差;充分利用HSI颜色空间中颜色分量与明度分量的独立性,对明度分量进行自适应的局部直方图均衡化,进一步提升图像的对比度和清晰度。主、客观的实验数据显示,相对于部分现有方法,本文方法对水下图像增强后的视觉效果更优,信息熵、平均梯度、水下图像质量指标(Underwater Image Quality Measures, UIQM)和结构相似性指数(Structural Similarity Index Measure, SSIM)的值更高。因此,本文方法对水下图像具有更有优的增强效果。

     

    Abstract: To improve the color of underwater imaging more effectively, and enhance the contrast and clarity of images, an underwater image enhancement method based on improved histogram matching and adaptive equalization is proposed. Each channel image is subjected to histogram matching using the histogram of the channel image with the largest pixel mean as the benchmark to correct the color deviation of the underwater image; taking full advantage of the independence of the color and lightness components in the HSI color space, this method performs an adaptive local histogram equalization on the lightness component, further improving the contrast and clarity of the image. Subjective and objective experimental data show that compared with some existing methods, the proposed method achieves better visual effects on underwater images after enhancement, with higher information entropy, an average gradient, UIQM, and SSIM. Therefore, the proposed method has a better enhancement effect on underwater images.

     

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