Real time image de-blurring and image stitching for muscle inspired camera orientation system
Sean A. Kilbride, Michael D. Kim, Jun Ueda · 2014
This paper proposes a method for real-time image de-blurring and panoramic image stitching. Currently there are several methods for de-blurring images and images stitching however, many take several seconds to process on a standard computer. The method proposed in this paper is to implement parallel processing techniques to an existing de-blurring method and a new dynamic-based panoramic image stitching method to achieve real-time image processing. This method has been applied to a muscle inspired camera orientation system that rapidly captures images to process these images in real time. This orientation system captures images while the camera is in motion causing a blurring effect. Using estimated position data from the system dynamics of the camera orientation system the point spread function of the image and the average image location can be estimated; hence, the image is de-blurred and stitched in real time. The proposed method makes use of parallel processing and precomputation techniques to greatly reduce the required processing time when compared to existing methods.