Method for quantitatively evaluating illumination consistency of remote sensing images

Abstract

The invention discloses a method for quantitatively evaluating the illumination consistency of remote sensing images. The method is used for extracting elevation information from each single remote sensing image on the basis of dark channels and bilateral filtering, and includes a first step of estimating air light vectors: computing dark channel images of the inputted images, extracting the front 0.1% pixels, which have the highest brightness, of all pixels from the dark channel images, and acquiring the pixels with the highest intensity in the previously acquired pixels in the inputted images to be used as the air light vectors; and a second step of computing optimized transmission images and computing depth-of-field images: computing dark images, computing a local mean value and a local standard deviation of each dark channel image, computing the difference between the local mean value and the local standard deviation of each dark channel image to obtain an atmosphere light curtain, and subtracting a quotient of each atmosphere light curtain to a mean value of the air light vectors from 1 to obtain the corresponding field-of-depth image. Each dark image corresponds to the minimum one of three channels of the corresponding color image. Heights of photographic fields in the images can be estimated by the aid of the depth-of-field images.

Description

technical field [0001] The invention belongs to a quantitative evaluation method, in particular to a quantitative evaluation method for illumination consistency of remote sensing images. Background technique [0002] The high-resolution image comparison method is a simple and effective method in image quality evaluation, and its premise is that the two high-resolution and low-resolution images used for comparison have good consistency. However, the actual situation is often difficult to meet these consistency requirements. In order to make the images that cannot meet the illumination consistency can also be used for satellite on-orbit parameter monitoring, it is necessary to perform illumination consistency correction. At present, there is no complete system for image illumination consistency correction. Most of the methods are to extract illumination invariants in face recognition, or use gamma correction, Retinex and other methods to eliminate excessive or too dark in a si...

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Problems solved by technology

At present, there are many illumination consistency correction methods (1. Zhu Shulong, Zhang Zhen, Zhu Baoshan, Cao Wen. Comparison of the effects of remote sensing image brightness and contrast distribution inhomogeneity correction algorithms. Journal of Remote Sensing. 2011,15(1): 111 -122.2. Huifang Li, Huanfeng Shen, Liangpei Zhang, Pingxiang Li. A Variational Retinex-based Inhomogeneity Correction Method for Remote Sensing Imagery. Acta Surveying and Mapping. 2010, vol.39: 585-598), but the correction results of these methods can only be obtained from Evaluate subjectively, lack of quantitative analysis, and quantitative evaluation methods are essential for comparing the effects of illumination consistency correction methods

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