Abstract: A fast, accurate and efficient Gaussian filter implements a box filter implementation, applies the central limit theorem and uses an overflow implementation. By combining the box filter, central limit theorem and overflow, the filter is fast, accurate and efficient so that it is able to be implemented in hardware and/or software easily.

Abstract: Tunable Gaussian filters enable imaging effects to be applied to images and videos in orientations other than standard symmetric, 0 degree orientations and 90 degree orientations. The tunable Gaussian filters are able to be applied in any orientation such as 45 degrees, slightly less than 45 degrees and slightly more than 0 degrees.

Abstract: A two picture matching curve information is able to be used to determine precise object distance or relative object distance in a scene. Acquiring two images with different blur information in addition to the curve information enables a device to determine distance information of objects in a scene. The distance information is able to be used in image processing including generating a depth map which is then able to be used in many imaging applications.

Abstract: Tunable Gaussian filters enable imaging effects to be applied to images and videos in orientations other than standard symmetric, 0 degree orientations and 90 degree orientations. The tunable Gaussian filters are able to be applied in any orientation such as 45 degrees, slightly less than 45 degrees and slightly more than 0 degrees.

Abstract: Apparatus and method for electronically estimating focusing distance between a camera (still and/or video camera) and a subject. Images at different focal positions of a calibration target are collected with distances between subject positions. In one aspect, histogram matching is performed to reduce noise error. A focus matching model is then generated in response to detected blur differences between successive images of the calibration target. The focus matching model is preferably converted to a polynomial equation of a desired order to smooth out image collection noise. The focus matching model is stored for access during operation. In use, the distance to subject is estimated in response to capturing images, detecting blur differences between the images and entering the blur difference information into the matching model.

Abstract: A method of and system for computing control points in a test target are described herein. The method and system utilize symmetry to test pixel locations in a raster scan fashion, then a computed Sum of Absolute Differences or a Sum of Squared Difference value is stored at the pixel locations, which enables identification of local minimum in the resulting surface. The local minimum are control point locations.

Abstract: A fast, accurate and efficient Gaussian filter implements a box filter implementation, applies the central limit theorem and uses an overflow implementation. By combining the box filter, central limit theorem and overflow, the filter is fast, accurate and efficient so that it is able to be implemented in hardware and/or software easily.

Abstract: Camera depth estimation is performed in response to picture matching based on blur difference computed between images captured at different focal positions. A blur difference model is stored in the camera based on characterization of the camera with a series of matching curves in which blur difference varies depending on the focal length, aperture, subject distance, and lens focus position. A four-dimensional polynomial model is created to fit the matching curves for use in estimating subject distance. During operation, images are captured for use in estimating subject distance. Motion compensation is applied and blur difference is determined. Blur difference is utilized in the polynomial model to estimate subject distance. Subject distance estimates can be output or utilized within an auto focus process to provide accurate focus adjustments.

Abstract: Camera depth estimation is performed in response to picture matching based on blur difference computed between images captured at different focal positions. A blur difference model is stored in the camera based on characterization of the camera with a series of matching curves in which blur difference varies depending on the focal length, aperture, subject distance, and lens focus position. A four-dimensional polynomial model is created to fit the matching curves for use in estimating subject distance. During operation, images are captured for use in estimating subject distance. Motion compensation is applied and blur difference is determined. Blur difference is utilized in the polynomial model to estimate subject distance. Subject distance estimates can be output or utilized within an auto focus process to provide accurate focus adjustments.

Abstract: A two picture matching curve information is able to be used to determine precise object distance or relative object distance in a scene. Acquiring two images with different blur information in addition to the curve information enables a device to determine distance information of objects in a scene. The distance information is able to be used in image processing including generating a depth map which is then able to be used in many imaging applications.

Abstract: Apparatus and method for electronically estimating focusing distance between a camera (still and/or video camera) and a subject. Images at different focal positions of a calibration target are collected with distances between subject positions. In one aspect, histogram matching is performed to reduce noise error. A focus matching model is then generated in response to detected blur differences between successive images of the calibration target. The focus matching model is preferably converted to a polynomial equation of a desired order to smooth out image collection noise. The focus matching model is stored for access during operation. In use, the distance to subject is estimated in response to capturing images, detecting blur differences between the images and entering the blur difference information into the matching model.

Abstract: A system and method for efficiently performing a depth map recovery procedure includes an imaging device that is implemented in a single-lens stereo-shutter configuration for simultaneously capturing overlaid images corresponding to a photographic target. A depth map generator is configured to analyze the overlaid images to determine disparity values corresponding to separation distances between matching points in the overlaid images. The depth map generator then utilizes the disparity values to calculate depth values that correspond to locations in the photographic target. The depth map generator may then utilize the foregoing depth values for creating a depth map corresponding to the photographic target.

Abstract: An imaging acquisition system that generates a picture depth from an auto focus curve generated from picture of a three dimensional spatial scene is described. The auto focus curve comprises a step edge. The system generates the depth based on the step edge and a reference auto focus normalization curve.

Abstract: A method to simultaneously generate and capture a plurality of blurred images utilizing a camera lens and a plurality of imaging sensors is described. A signal passes through a lens and is then split into a plurality of signal paths of different lengths using a signal splitting device. Since the physical distances between the lens and the plurality of imaging sensors are different, with different signal path lengths, a plurality of uniquely blurred images are captured by the plurality of imaging sensors. Utilizing the plurality of blurred images, computations are performed and blur differences are calculated. A depth map is then determined from the blur differences. With the depth map, a number of applications are possible.

Abstract: An imaging acquisition system that generates a depth map from two pictures of a three dimensional spatial scene is described. According to one aspect of the invention, the system generates the depth map based on the relative blur between the two pictures and the absolute blur contributed by the system. According to another aspect of the invention, the system calculates the depth map directly from the relative blur between the two pictures.

Abstract: An imaging acquisition system that generates a depth map for a picture of a three dimension spatial scene from the estimated blur radius of the picture is described. The system generates an all-in-focus reference picture of the three dimension spatial scene. The system uses the all-in-focus reference picture to generate a two-dimensional scale space representation. The system computes the picture depth map for a finite depth of field using the two-dimensional scale space representation.

Abstract: A system and method for efficiently performing a depth map recovery procedure includes an imaging device that is implemented in a single-lens stereo-shutter configuration for simultaneously capturing overlaid images corresponding to a photographic target. A depth map generator is configured to analyze the overlaid images to determine disparity values corresponding to separation distances between matching points in the overlaid images. The depth map generator then utilizes the disparity values to calculate depth values that correspond to locations in the photographic target. The depth map generator may then utilize the foregoing depth values for creating a depth map corresponding to the photographic target.

Abstract: A display panel image stabilization method and apparatus includes enabling a user to adjust both the pixel clock pulses and the synchronization for the display panel simultaneously by a single control. The synchronization is adjusted in a stepwise manner through a given number of steps for a particular number of clock pulses. The image is observed by the user to determine whether or not the noise stripes are being eliminated. The stepwise adjustment of the synchronization is repeated for another particular number of clock pulses if the noise stripes are not being eliminated. Once all of the stripes have been eliminated from the image, both the synchronization and the pixel clock pulses are properly adjusted to stabilize the image.