KEYWORDS: Modulation transfer functions, Image restoration, Filtering (signal processing), Sensors, Electronic filtering, Optical transfer functions, Signal to noise ratio, Image sensors, Fourier transforms, Linear filtering
In this paper we investigate the influence of motion sensor errors on the derivation of the MTF and its implementation in image restoration. We present an analytical approach for estimating the vibration MTF from the measured system MTF by the frequency response of the sensor and their noise data. The goal of this research is to describe an automatic system of restoration of pictures blurred by vibration, and to consider its possible disadvantages. Our method is based on point-spread function verification by the data of motion sensor characteristics. We build an analytical model of the sensor and compare the MTF after sensor errors caused by noise of the system and wrong axis direction of the restoration device. Here, we assume that noise and signal are independent and noise of the system is white Gaussian noise. Some image restoration of degraded images is presented based on improvements of the original wiener filter. We compare performance of inverse and wiener filter operations and consider the dependence of restoration quality on the signal to noise ratio and angel between restoration axis and true vibration direction. There is an interesting and useful relationship in the final graphs. This article brings us to improvement of the initial method, as seen from our simulation. Some restorations of degraded images are presented based on improvements of the original wiener filter. The key to the restoration is determination of the improved optical transfer function unique to the image vibration and sensor characteristics.