Abstract
The improper setting of exposure time for the space camera will cause serious image quality degradation (overexposure or underexposure) in the imaging process. In order to solve the problem of insufficient utilization of the camera’s dynamic range to obtain high-quality original images, an automatic exposure method for plane array remote sensing images based on two-dimensional entropy is proposed. First, a two-dimensional entropy-based image exposure quality evaluation model is proposed. The two-dimensional entropy matrix of the image is partitioned to distinguish the saturated areas (region of overexposure and underexposure) and the unsaturated areas (region of propitious exposure) from the original image. The ratio of the saturated area is used as an evaluating indicator of image exposure quality, which is more sensitive to the brightness, edges, information volume, and signal-to-noise ratio of the image. Then, the cubic spline interpolation method is applied to fit the exposure quality curve to efficiently improve the camera’s exposure accuracy. A series of experiments have been carried out for different targets in different environments using the existing imaging system to verify the superiority and robustness of the proposed method. Compared with the conventional automatic exposure method, the signal-to-noise ratio of the image obtained by the proposed algorithm is increased by at least 1.6730 dB, and the number of saturated pixels is reduced to at least 2.568%. The method is significant to improve the on-orbit autonomous operating capability and on-orbit application efficiency of space camera.
Highlights
With the rapid development of space remote sensing technology, the strong demand for satellite responsiveness and imaging quality are increasing [1]
It has a high dynamic range (HDR) and large area of the shooting scene, and the obtained remote sensing image has a large amount of data and rich details which all lead to higher exposure quality of the space camera [2,3]
The rest of the paper is organized as follows: the automatic exposure method for plane array remote sensing images based on two-dimensional entropy is proposed in Section 2; in Section 3, the proposed algorithm is experimentally compared with other algorithms and related discussions are carried out; Section 4 presents the conclusions of the paper
Summary
With the rapid development of space remote sensing technology, the strong demand for satellite responsiveness and imaging quality are increasing [1]. Effective image fusion methods require multiple pre-acquired images of different dynamic range [9], for the shooting target under extreme lighting conditions is poor Another method is to establish the mathematical relationships between image quality indices and imaging parameters through the analysis of image statistics, thereby adjusting the camera’s imaging parameters such as shutter speed, aperture size, exposure time, and gain. Set a target brightness and adjust the imaging parameters to make the brightness level of the image gradually consistent with the target brightness This method based on the average gray value of the image could cause a large area of overexposure and underexposure at the same time, resulting in the loss of a large amount of image details. The rest of the paper is organized as follows: the automatic exposure method for plane array remote sensing images based on two-dimensional entropy is proposed in Section 2; in Section 3, the proposed algorithm is experimentally compared with other algorithms and related discussions are carried out; Section 4 presents the conclusions of the paper
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