Real-time image de-blurring and image processing for a robotic vision system

Abstract

This paper proposes a method for real-time deblurring of images captured by a robotic system. De-blurring is achieved by combining a dynamics-based approach and parallel computing. Existing methods have successfully restored a blurry image but were not suitable for real-time applications. The dynamics-based method with parallel programming in the FPGA is used to estimate the PSF during the camera exposure window. The deconvolution process, which involves iterative matrix calculations with millions of pixels, is then performed on the GPU to achieve real-time performance. The proposed method has been evaluated by using a robotic system which has a total of 32 piezoelectric actuators and one vision sensor. The frame rate of image de-blurring ranges from 20.32 to 40.68 fps and thus real-time performance is achieved. In comparison to existing methods, the proposed method produces the best image quality. The dynamics-based approach is extended to real-time image stitching which is computationally cheap and robust to motion blur. It is demonstrated from image stitching that real-time de-blurring is beneficial for image processing.

Blind and Non-Blind Deconvolution-Based Image Deblurring Techniques for Blurred and Noisy Image

“…Due to this issue, numerous academics have been trying to determine the best method for deblurring and restoring an image [6]. A method for deblurring photographs taken by a robotic system in realtime has been proposed by Kim and Ueda [7], Deblurring is performed by combining a dynamics-based technique with parallel computing, allowing deblurring. Although existing techniques have recovered a blurred image satisfactorily, they are unsuitable for real-time applications.…”

Improved estimation of motion blur parameters for restoration from a single image

“…As one of the main causes of image degradation, it seriously affects the performances of computer vision system in various fields. So efficient motion deblurring technology is conducive to improving the reliability of related applications, such as aerospace, medical imaging, traffic monitoring, public safety, military search, satellite and space image [1][2][3].…”