سابِق|تال

Adaptive dodging method based on variational mask for remote sensing images

  • role： First author第一作者
  • Affiliation：

    Institute of Surveying and Mapping, Information Engineering University, Zhengzhou 450001, China

  • Email：chxyls@163.com
  • Introduction：李烁(1990—　)，男，博士研究生，研究方向为数字摄影测量和数字图像处理。E-mail：chxyls@163.com
Shuo LI,  
  • Affiliation：

    Institute of Surveying and Mapping, Information Engineering University, Zhengzhou 450001, China

Hui WANG,  
  • Affiliation：

    Institute of Surveying and Mapping, Information Engineering University, Zhengzhou 450001, China

Liyong WANG,  
  • Affiliation：

    Institute of Surveying and Mapping, Information Engineering University, Zhengzhou 450001, China

Xiangzhou YU,  
  • Affiliation：

    Institute of Surveying and Mapping, Information Engineering University, Zhengzhou 450001, China

Le YANG

ملخص

The illumination of a captured remote sensing image may be unevenly distributed because of the influences of sensors and external factors, such as light and fog. Uneven illumination degrades the quality of an image and causes interference in the subsequent processing (e.g., image interpretation, image classification, and image mosaicking). The process of correcting uneven illumination is called image dodging, which is of great practical significance and application value. Current methods focus on how to obtain the illumination distribution within an image and compensate for the different parts of the image in different degrees. The mask dodging method is widely used for remote sensing images. The background is generated by a low-pass filter to simulate the illumination distribution and subtracted from the original image to obtain the ideal image with even illumination. Estimation of the background image is a key step in the mask dodging method and directly affects the resulting image, which depends on the low-pass filter and its dimension parameter. Automatic selection of the dimension parameter is a problem in the mask dodging method. However, no suitable solution to the problem exists, and manual adjustment is usually required in practical applications. An adaptive dodging method based on a variational mask is proposed in this study to resolve the poor universality of the mask dodging method. A variational energy function is constructed according to the prior information of the image itself and the mathematical model of the mask dodging method. L1 and L2 norms are adopted to constrain the texture and detail of the ideal image and the smoothness of the background image, respectively. Estimation of the background image is transformed into an optimal solution of the variational energy function. Solving the problem directly is often difficult because the variational function contains two norms. The split Bregman method is used to decompose the variational function into three subproblems, which are solved by alternate iteration, to simplify the calculation. Optimal background and ideal images are then obtained simultaneously. Two groups of experiments are conducted on three remote sensing images to verify the effectiveness of the proposed method. Compared with mask dodging methods with three different dimension parameters, the proposed method performs better in visual evaluation and quantitative measurements. The proposed method can effectively eliminate uneven illumination while maintaining the textures and details of the remote sensing images.

مفهوم

image dodging;variational Mask;uneven illumination;background image;split Bregman

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