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...

A layered motion estimation scheme using fuzzy clustering is introduced in this papel: Once motion estimation is performed, a modified objective criterion is applied to discard non sign$cant classes.

Digital image stabilization (DIS) is the process that compensates the undesired fluctuations of a frame’s position in an image sequence by means of digital image processing techniques. DIS techniques usually comprise two successive units. The first one estimates the motion and the successive one compensates it. In this paper, a novel digital image stabilization technique is proposed, which is f...

Digital video stabilization (DVS) allows acquiring video sequences without disturbing jerkiness, removing unwanted camera movements. A good DVS should remove the unwanted camera movements while maintains the intentional camera movements. In this article, we propose a novel DVS algorithm that compensates the camera jitters applying an adaptive fuzzy filter on the global motion of video frames. T...

Neural fuzzy systems can improve motion estimation and compensation for video compression. Motion estimation and compensation are key parts of video compression. They help remove temporal redundancies in images. But most motion estimation algorithms neglect the strong temporal correlations of the motion field. The search windows stay the same through the image sequences and the estimation needs...

Digital video stabilization (DVS) allows acquiring video sequences without disturbing jerkiness, removing unwanted camera movements. A good DVS should remove the unwanted camera movements while maintains the intentional camera movements. In this article, we propose a novel DVS algorithm that compensates the camera jitters applying an adaptive fuzzy filter on the global motion of video frames. T...

A layered motion estimation scheme using fuzzy clustering is introduced in this paper. Once motion estimation is performed, a label smoothing is applied by using a modified objective function that takes into account spatial continuity. This allows to suppress noisy classes scattered over the

This paper presents a new fuzzy framework for main motion estimation in video sequences. The estimation is performed using a fuzzy representation of pixel gray levels. The motion is characterized by a set of parameters such as horizontal translation, rotation, etc. The method is based on a Hough-like vote procedure. In this scheme, the parametric space is discretized and each pixel votes for ea...

In this paper we present a technique which infers interframe motion by tracking SIFT features through consecutive frames: feature points are detected and their stability is evaluated through a combination of geometric error measures and fuzzy logic modelling. Our algorithm does not depend on the point detector adopted prior to SIFT descriptor creation: therefore performance have been evaluated ...

A novel digital image stabilization technique is proposed in this paper. It is based on a fuzzy Kalman compensation of the global motion vector (GMV), which is estimated in the log-polar plane. The GMV is extracted using four local motion vectors (LMVs) computed on respective subimages in the logpolar plane. The fuzzy Kalman system consists of a fuzzy system with the Kalman filter’s discrete ti...