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Using mainifest to improve a grayscale method based on Color-to-gray conversion using ISOMAP [Cui et al. 2010]

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图像灰度化 Image Grayscale

本文的图像灰度化实现主要基于:

  1. Data-driven Color Manifolds [Nguyen et al. 2015].
  2. Color-to-gray conversion using ISOMAP [Cui et al. 2010].
  3. 一种快速映射Isomap算法 [圣少友 et al. 2009].

使用方法:

install

pip install SOMGraySclae==1.0.1
获取灰度图
gray, gray_reverse = som.get_gray_scal(os.path.dirname(__file__) + '/datasets/apple/apple_0.png')
plt.imsave(os.path.dirname(__file__) + '/gray.png', gray, cmap='gray',vmin = 0, vmax = 1)
plt.imsave(os.path.dirname(__file__) + '/gray_reverse.png', gray, cmap='gray', vmin=0, vmax=1)
获取一维流形:
som = SOMGraySclae()
manifest_1d = som.get_1d_manifold(os.path.dirname(__file__) + '/datasets/apple/apple_0.png')
plt.imsave(os.path.dirname(__file__) + '/manifest_1d.png', manifest_1d, cmap='gray', vmin=0, vmax=1)
获取二维流形:
som = SOMGraySclae()
manifest_2d = som.get_2d_manifold(os.path.dirname(__file__) + '/datasets/apple/apple_0.png')
plt.imsave(os.path.dirname(__file__) + '/manifest_2d.png', manifest_2d, cmap='gray', vmin=0, vmax=1)
获取debug plt:
som = SOMGraySclae()
som.color_to_gray_debug(os.path.dirname(__file__) + '/datasets/apple/apple_0.png',
                   gray_name='gray', gray_reverse_name='gray_reverse', debug=True)    

灰度化结果

输入图像:

获取灰度图,输出图像:

*

for debug:

所有结果:

感谢

项目中采用Nguyen等人的论文实现,基于以下开源项目: https://github.com/tody411/SOM-ColorManifolds

License

The MIT License 2017 (c) tody

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Using mainifest to improve a grayscale method based on Color-to-gray conversion using ISOMAP [Cui et al. 2010]

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