A new method of calculating the optical transfer function (OTF) for image blur caused by arbitrary motion is introduced. Previous methods, except for a few specific types of motion, were numerical rather than analytical. This new method makes it possible to obtain analytical expressions for the OTF deriving from any kind of motion by means of the statistical moments of the motion function. Anal...

Subject motion during the time course of functional activation studies has been shown to cause spurious signals which can mimic 'true' activation. Therefore, the importance of motion correction has been widely recognized. Correction with post-processing using image registration software is common practice in functional imaging and analysis. Many image registration algorithms, developed for anal...

Abs t rac t . A robust method is introduced for computing the camera motion (the ego-motion) in a static scene. The method is based on detecting a single planar surface in the scene directly from image intensities, and computing its 2D motion in the image plane. The detected 2D motion of the planar surface is used to register the images, so that the planar surface appears stationary. The result...

In this thesis novel algorithms for the segmentation and classification of video objects are developed. The segmentation procedure is based on motion and is able to extract moving objects acquired by either a static or a moving camera. The classification of those objects is performed by matching their outlines gathered from a number of consecutive frames of the video with preprocessed views of ...

In many autonomous mobile applications, robots must be capable of analyzing motion of moving objects in their environment. Duringmovement of robot the quality of images is affected by quakes of camera which cause high errors in image processing outputs. In thispaper, we propose a novel method to effectively overcome this problem using Neural Networks and Kalman Filtering theory. Thistechnique u...

The goal of multi-frame Super Resolution (SR) is to fuse multiple Low Resolution (LR) images to produce one High Resolution (HR) image. The major challenge of classic SR approaches is accurate motion estimation between the frames. To handle this challenge, fuzzy motion estimation method has been proposed that replaces value of each pixel using the weighted averaging all its neighboring pixels i...

Motion estimation is the process which determine motion vectors that describe the transformation from one 2D image to another from adjacent frames in a video sequence. It is the motion is in three dimensions but the images are a projection of the 3D scene onto a 2D plane. By motion estimation, we mean the estimation of the displacement or velocity of image structures from one frame to another i...

People perceive any kind of information with different level of attention and involvement. It is due to the way how our brain functions, redundancy and importance of the perceived data. This work deals with visual information, in particular with images. Image analysis and processing is often requires running computationally expensive algorithms. The knowledge of which part of an image is import...

1. Background and motivation Multi-dimensional image processing is of paramount importance in areas such as multimedia, robotics, computer vision, graphics, biomedical engineering and industrial inspection. The growing interest in the development of multi-dimensional image processing techniques should be attributed primarily to the importance of color image and video processing and analysis. Pr...