Abstract: Example methods and apparatus to capture compressed images are disclosed. A disclosed example method includes capturing a first output of a first photodetector representative of a first weighted sum of the a plurality of portions of an image, capturing a second output of a second photodetector representative of a second weighted sum of a second plurality of portions of the image, and computing a first wavelet coefficient for the image using the first and second captured outputs.

Abstract: Certain embodiments of the present invention provide a system for computer vision including a plurality of images, a signature processor adapted to generate a signature based at least in part on a curvelet transform, and a matching processor adapted to receive a query image. The matching processor is adapted to determine a query signature for the query image using the signature processor. The matching processor is adapted to determine at least one matching image from the plurality of images based at least in part on the query signature.

Abstract: A lossless image streaming system for the transmission of images over a communication network. The system eliminates the necessity to store a compressed version of the original image, by losslessly streaming ROI data using the original stored image. The imaging system also avoids the computationally intensive task of compression of the full image. When a user wishes to interact with a remote image, the imaging client generates and sends a ROI request list to the imaging server. The request list can be ordered according to the particular progressive mode selected (e.g., progressive by quality, resolution or spatial order). The imaging server performs a fast preprocessing step in near real time after which it can respond to any ROI requests in near real time. When a ROI request arrives at the server, a progressive image encoding algorithm is performed, but not for the full image. Instead, the encoding algorithm is performed only for the ROI.

Abstract: Certain embodiments provide systems and methods for using geometric wavelets based on active contours for signal processing. Certain embodiments may allow image processing. A system includes providing an image processing circuitry that computes a segmentation tree using active contours for an input image data; creates a geometric wavelets representation using the segmentation tree; and then generate an image based on geometric wavelet sparse representation extracted from the geometric wavelets representation. The geometric wavelet sparse representation may comprise M most active geometric wavelets from a set of N geometric wavelets in the geometric wavelets representation. The image processing circuitry may recursively find sub-domains and multivariate polynomials for each domain at each stage in the computing of the segmentation tree. Each of the sub-domains is a domain for a succeeding stage for the segmentation tree.

Abstract: In a system for transmitting a three-dimensional (3-D) digital image over a communication network, in response to a client computer generating a request for interaction with a 3-D image stored on an image storage device, a server computer performs two-dimensional sub-band transform decompositions in x-axis and y-axis directions upon the 3-D image, performs a one-dimensional sub-band transform decomposition in a z-axis direction upon a portion of the two-dimensionally transform-decomposed digital image, and progressively transmits to the client computer data representing a region of interest specified in the client request.

Abstract: A Picture Archiving and Communications System (PACS) transmits medical image information from a server to a viewing workstation. The mode of transmission that the system uses depends on a performance metric of the network. If the network is fast and stable, the entire DICOM image file is transmitted. If the network is not fast and stable, one of several other modes is used to transmit the image information.

Abstract: A lossless image streaming system for the transmission of images over a communication network. The system eliminates the necessity to store a compressed version of the original image, by losslessly streaming ROI data using the original stored image. The imaging system also avoids the computationally intensive task of compression of the full image. When a user wishes to interact with a remote image, the imaging client generates and sends a ROI request list to the imaging server. The request list can be ordered according to the particular progressive mode selected (e.g., progressive by quality, resolution or spatial order). The imaging server performs a fast preprocessing step in near real time after which it can respond to any ROI requests in near real time. When a ROI request arrives at the server, a sophisticated progressive image encoding algorithm is performed, but not for the full image. Instead, the encoding algorithm is performed only for the ROI.

Abstract: A lossless image streaming system for the transmission of images over a communication network. The system eliminates the necessity to store a compressed version of the original image, by losslessly streaming ROI data using the original stored image. The imaging system also avoids the computationally intensive task of compression of the full image. When a user wishes to interact with a remote image, the imaging client generates and sends a ROI request list to the imaging server. The request list can be ordered according to the particular progressive mode selected (e.g., progressive by quality, resolution or spatial order). The imaging server performs a fast preprocessing step in near real time after which it can respond to any ROI requests in near real time. When a ROI request arrives at the server, a progressive image encoding algorithm is performed, but not for the full image. Instead, the encoding algorithm is performed only for the ROI.

Abstract: Disclosed is a lossless image streaming system for the transmission of images over a communication network. The system eliminates the necessity to store a compressed version of the original image, by losslessly streaming ROI data using the original stored image. The imaging system of the present invention also avoids the computationally intensive task of compression of the full image. When a user wishes to interact with a remote image, the imaging server performs a fast preprocessing step in near real time after which it can respond to any ROI requests also in near real time. When a ROI request arrives at the server, a sophisticated progressive image encoding algorithm is performed, but not for the full image. Instead, the encoding algorithm is performed only for the ROI.

Abstract: In a system for transmitting a three-dimensional (3-D) digital image over a communication network, in response to a client computer generating a request for interaction with a 3-D image stored on an image storage device, a server computer performs two-dimensional sub-band transform decompositions in x-axis and y-axis directions upon the 3-D image, performs a one-dimensional sub-band transform decomposition in a z-axis direction upon a portion of the two-dimensionally transform-decomposed digital image, and progressively transmits to the client computer data representing a region of interest specified in the client request.

Abstract: Disclosed is a lossless image streaming system for the transmission of images over a communication network. The system eliminates the necessity to store a compressed version of the original image, by losslessly streaming ROI data using the original stored image. The imaging system of the present invention also avoids the computationally intensive task of compression of the fall image. When a user wishes to interact with a remote image, the imaging server performs a fast preprocessing step in near real time after which it can respond to any ROI requests also in near real time. When a ROI request arrives at the server, a sophisticated progressive image encoding algorithm is performed, but not for the full image. Instead, the encoding algorithm is performed only for the ROI.

Abstract: The imaging system that is described below is an image streaming system which is different from traditional compression systems. It eliminates the necessity to store a compressed version of the original image, by streaming ROI data using the original stored image. The imaging system of the present invention also avoids the computationally intensive task of compression of the full image. Instead, once a user wishes to interact with a remote image, the imaging server performs a fast preprocessing step in near real time after which it can respond to any ROI requests also in near real time. When a ROI request arrives at the server, a sophisticated progressive image encoding algorithm is performed, but not for the full image. Instead, the encoding algorithm is performed only for the ROI.