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Joint Method of Interference Suppression and Super-Resolution for Chinese Characters Image with Interference

机译：具有干扰的汉字图像的干扰抑制与超分辨率联合方法

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摘要

As Chinese characters image often has insufficient photography illumination, or underlines under characters, or low resolution, a joint method of interference suppression and super-resolution for Chinese characters image with interference is proposed. In the stage of interference suppression preprocessing, the technology of image layer separation is used to decompose Chinese characters image into the illumination layer and reflectance layer at first, and reflectance layer that contains the essential property of input image is retained consequently. Then the reflectance layer is decomposed into four coefficient subimages by wavelet transform, and image smoothing via L-0 gradient minimization with different scale factors is adopted to these different coefficient subimages. Subsequently, by a simple background processing and image filtering, the image preprocessing for Chinese characters image with interference is ultimately completed. In the stage of image super-resolution, due to acquisition limitation of a large number of high-resolution Chinese characters images, we adopt neighbor embedding super-resolution method for its advantage of greatly reducing the scale of training set. In the key feature vector of Chinese characters image, the weights of horizontal and vertical stroke features are strengthened; meanwhile, the other stroke features of Chinese characters are also considered. Ultimately, a super-resolution method more suitable for Chinese characters image is proposed. Experimental results show that our method of interference suppression has the superiority for Chinese characters images with aforementioned interference, and our optimized super-resolution method has better performance for test Chinese characters images than bicubic interpolation method and three classical super-resolution methods.
机译：由于汉字图像通常没有足够的摄影照度，或者在汉字下划线，或者分辨率较低，因此提出了一种对具有干扰的汉字图像进行干扰抑制和超分辨率的联合方法。在干扰抑制预处理阶段，首先采用图像层分离技术将汉字图像分解为照明层和反射层，从而保留了包含输入图像本质的反射层。然后，通过小波变换将反射层分解为四个系数子图像，并对这些不同系数子图像采用通过L-0梯度最小化对不同比例因子进行图像平滑。随后，通过简单的背景处理和图像过滤，最终完成了对带有干扰的汉字图像的图像预处理。在图像超分辨率阶段，由于大量的高分辨率汉字图像的采集限制，我们采用邻居嵌入超分辨率方法，因为其优点是大大减少了训练集的规模。在汉字图像的关键特征向量中，水平和垂直笔画特征的权重得到增强；同时，还考虑了汉字的其他笔画特征。最终，提出了一种更适合汉字图像的超分辨率方法。实验结果表明，我们的干扰抑制方法在具有上述干扰的汉字图像方面具有优越性，并且优化的超分辨率方法在测试汉字图像方面具有比双三次插值方法和三种经典超分辨率方法更好的性能。

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  • 来源
    《Mathematical Problems in Engineering》 |2018年第14期|4203121.1-4203121.17|共17页
  • 作者

    Jiang Bo; Hu Wei; Liang Jian; Zhang Shouxu; Ma Xiaolei; Zhou Yan; Niu Jinping; Chen Xiaoxuan;

  • 作者单位

    Northwest Univ, Sch Informat Sci & Technol, Xian 710127, Shaanxi, Peoples R China;

    Northwest Univ, Sch Informat Sci & Technol, Xian 710127, Shaanxi, Peoples R China;

    Chinese Acad Sci, State Key Lab Transient Opt & Photon, Xian 710119, Shaanxi, Peoples R China;

    Northwestern Polytech Univ, Sch Marine Sci & Technol, Xian 710072, Shaanxi, Peoples R China;

    Emory Univ, Dept Phys, Atlanta, GA 30322 USA;

    Northwest Univ, Sch Informat Sci & Technol, Xian 710127, Shaanxi, Peoples R China;

    Northwest Univ, Sch Informat Sci & Technol, Xian 710127, Shaanxi, Peoples R China;

    Northwest Univ, Sch Informat Sci & Technol, Xian 710127, Shaanxi, Peoples R China;

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