Abstract
In remote-sensing imaging, the modulation transfer function (MTF) for image motion relevant to the mixing of multiple forms of motions is hard to calculate because of the complicated image motion expression. In this paper, a new method for calculating the MTF for complex image motion is proposed. The presented method makes it possible to obtain an analytical MTF expression derived from the mixing of linear motion and sinusoidal motion at an arbitrary frequency. On this basis, we used the summation of infinitely many terms involving the Bessel function to simplify the MTF expression. The truncation error obtained by the use of finite order sum approximations instead of infinite sums is investigated in detail. In order to verify the MTF calculation method, we proposed a simulation method to calculate the variation of MTF in an actual optical system caused by image motion. The mean value of the relative error between the calculation method and the simulation method is less than 5%. The experimental results are consistent with the MTF curve calculated by our method.
Highlights
Nowadays, optical remote-sensing imaging is of interest for a wide variety of applications [1].In many types of vehicular or airborne imaging and in robotic systems, despite the use of high-quality sensors, the resolution is limited by the image motion [2,3,4] and, as a result, the high-resolution capability of the sensor may be wasted
In the design stage of the remote-sensing imaging instrument, an exact modulation transfer function (MTF) calculation model for complex image motion can make the allocation of instrument indicators more suitable [7,8]
This paper focuses on an analysis of the MTF decrease derived from the complex image motion, such as linear motion, low-frequency sinusoidal motion, and high-frequency sinusoidal motion, and builds a calculation model for it
Summary
Optical remote-sensing imaging is of interest for a wide variety of applications [1].In many types of vehicular or airborne imaging and in robotic systems, despite the use of high-quality sensors, the resolution is limited by the image motion [2,3,4] and, as a result, the high-resolution capability of the sensor may be wasted. It is considered that the influence of the image displacement on image quality is necessary in order to design the optical mechanical structure of the instrument, and is significant for further image restoration. It is very important to calculate the MTF for complex image motion accurately in order to provide significant theoretical guidance for instrument design and to increase the effect of image restoration. In the design stage of the remote-sensing imaging instrument, an exact MTF calculation model for complex image motion can make the allocation of instrument indicators more suitable [7,8]. In the process of the fuzzy restoration of remote-sensing images in the later stage, Wiener filtering and other restoration methods need to obtain accurate MTF values [9,10,11].
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