Abstract: A method of de-smearing an image includes capturing image data from an imaging sensor and collecting motion data indicative of motion of the sensor while capturing the image data. The motion data is collected at a higher frequency than an exposure frequency at which the image data is captured. The method includes modeling motion of the sensor based on the motion data, wherein motion is modeled at the higher frequency than the exposure frequency. The method also includes modeling optical blur for the image data, modeling noise for the image data, and forming a de-smeared image as a function of the modeled motion, the modeled blur, and the modeled noise, and the image data captured from the imaging sensor.

Abstract: A method of de-smearing an image includes capturing image data from an imaging sensor and collecting motion data indicative of motion of the sensor while capturing the image data. The motion data is collected at a higher frequency than an exposure frequency at which the image data is captured. The method includes modeling motion of the sensor based on the motion data, wherein motion is modeled at the higher frequency than the exposure frequency. The method also includes modeling optical blur for the image data, modeling noise for the image data, and forming a de-smeared image as a function of the modeled motion, the modeled blur, and the modeled noise, and the image data captured from the imaging sensor.

Abstract: An efficient object-detection-driven video data representation along with a unified content based video compression and retrieval framework and wavelet based searching engine is described to encode the disclosed video data representation. The video data representation and unified compression and retrieval and searching engine together facilitate rapid retrieval of desired video information from large stores of video data.

Abstract: An efficient object-detection-driven video data representation along with a unified content based video compression and retrieval framework and wavelet based searching engine is described to encode the disclosed video data representation. The video data representation and unified compression and retrieval and searching engine together facilitate rapid retrieval of desired video information from large stores of video data.

Abstract: Restoration based super-resolution combines a video sequence of low-resolution noisy blurred images using maximum likelihood estimation without regularization to produce a higher resolution image or video sequence up to a maximum enhancement factor r for the given video sequence. The maximum r value for a given sequence of low-resolution images that guarantees each high-resolution bin (pixel) will have at least one assigned pixel value from a low-resolution image is calculated. With the knowledge of max r, the system can select an r less than or equal to max r and thus operate without regularization. System robustness is further enhanced by providing a modified MLE estimator that can perform super resolution for arbitrary real-valued r so that enhancement is not limited to integer values.

Abstract: Restoration based super-resolution combines a video sequence of low-resolution noisy blurred images using maximum likelihood estimation without regularization to produce a higher resolution image or video sequence up to a maximum enhancement factor r for the given video sequence. The maximum r value for a given sequence of low-resolution images that guarantees each high-resolution bin (pixel) will have at least one assigned pixel value from a low-resolution image is calculated. With the knowledge of max r, the system can select an r less than or equal to max r and thus operate without regularization. System robustness is further enhanced by providing a modified MLE estimator that can perform super resolution for arbitrary real-valued r so that enhancement is not limited to integer values.

Abstract: A method is provided for a network including a plurality of nodes where a originating node broadcasts an address request or change PDU. When the PDU is received at a receiving node, the receiving node determines from a look-up routing table whether the broadcast PDU was received on an optimal interface, i.e. an interface which defines the shortest path between the originating and receiving nodes. If the interface was determined to be optimal, the receiving node forwards the request PDU along every interface belonging to the receiving node except the optimal interface, otherwise, the receiving node drops the request PDU. When node address information concerning the originating node cannot be obtained from the routing database of the receiving node, a unique medium node is located to assist in making the optimal interface determination. The method completely avoids the formation of loops thereby improving the performance of a telecommunication management network.