[19] F. Albu, L. Murray, P. Stec, I. Raducan, “Image rotation from local motion estimates”, US 8,705,894, April 22, 2014

ABSTRACT: A measure of frame-to-frame rotation is determined. Integral projection vector gradients are determined and normalized for a pair of images. Locations of primary maximum and minimum peaks of the integral projection vector gradients are determined. Based on normalized distances between the primary maximum and minimum peaks, a global image rotation is determined.

[18] A. Drimbarean, A. Zamfir, F. Albu, V. Poenaru, C. Florea, C. Bigioi, E. Steinberg, P. Corcoran, “Tone mapping for low-light video frame enhancement”, US 8,698,924, April 15, 2014

www.google.com/patents/US8698924

ABSTRACT: A technique is provided for generating sharp, well-exposed, color images from low-light images. A series of under-exposed images is acquired. A mean image is computed and a sum image is generated each based on the series of under-exposed images. Chrominance variables of pixels of the mean image are mapped to chrominance variables of pixels of the sum image. Chrominance values of pixels within the series of under-exposed images are replaced with chrominance values of the sum image. A set of sharp, well-exposed, color images is generated based on the series of under-exposed images with replaced chrominance values.

[17] F. Albu, A. Drimbarean, A. Zamfir, C. Florea, P. Corcoran, “Adaptive PSF estimation technique using a sharp preview and a blurred image”, US 8,649,628, February 11, 2014

www.google.com/patents/US8649628

ABSTRACT: An adaptive motion estimation and deblurring technique for acquired digital images includes acquiring multiple digital images with a moving digital image acquisition device that includes an image sensor, including a relatively sharp, underexposed reference image and a blurred image. Anb initial approximate point spread function (PSF) is estimated corresponding to the moving of the device. A different DC offset point is determined and a second PSF is calculated based on the different DC offset point.

[16] F. Albu, E. Steinberg, , P. Corcoran, A. Drimbarean, A. Zamfir, C. Florea, V. Poenaru, ”Image processing method and apparatus”, US 8,649,627, February 11, 2014

www.google.com/patents/US8649627

ABSTRACT: A method and apparatus for providing image processing. For one embodiment of the invention, an image processing apparatus is arranged to process a first relatively underexposed and sharp image of a scene, and a second relatively well exposed and blurred image, nominally of the same scene, the first and second images being derived from respective image sources. The apparatus provides a portion of the relatively first underexposed image as an input signal to an adaptive filter; and a corresponding portion of the second relatively well exposed image as a desired signal to the adaptive filter. The adaptive filter produces an output signal from the input signal and the desired signal; and an image generator constructs a first filtered image from the output signal, relatively less blurred than the second image.

[15] F. Albu, L. Murray, P. Stec, I. Raducan, ”Fast rotation estimation of objects in sequences of acquired digital images”, US 8,587,665, 19 November, 2013

www.google.com/patents/US8587665

ABSTRACT: A measure of frame-to-frame rotation is determined. A global XY alignment of a pair of frames is performed. Local XY alignments in at least two matching corner regions of the pair of images are determined after the global XY alignment. Based on differences between the local XY alignments, a global rotation is determined between the pair of frames.

[14] F. Albu, L. Murray, P. Stec, I. Raducan, ” Object detection from image profiles within sequences of acquired digital images”, US 8,587,666, 19 November, 2013

www.google.com/patents/US8587666

ABSTRACT: A measure of frame-to-frame rotation is determined. A global XY alignment of a pair of image frames is performed. At least one section of each of the X and Y integral projection vectors is determined, where aligned global vectors demonstrate a significant localized difference. Based on X and Y locations of the at least one section of the X and Y integral projection vectors, location, relative velocity and/or approximate area of at least one moving object within the sequence of image frames is/are determined.

[13] F. Albu, V. Poenaru, A. Drimbarean,“Autofocus method”, US 8,508,652, August13, 2013

www.google.com/patents/US8508652

ABSTRACT: An autofocus method includes acquiring multiple images each having a camera lens focused at a different focus distance. A sharpest image is determined among the multiple images. Horizontal, vertical and/or diagonal integral projection (IP) vectors are computed for each of the multiple images. One or more IP vectors of the sharpest image is/are convoluted with multiple filters of different lengths to generate one or more filtered IP vectors for the sharpest image. Differences are computed between the one or more filtered IP vectors of the sharpest image and one or more IP vectors of at least one of the other images of the multiple images. At least one blur width is estimated between the sharpest image and the at least one of the other images of the multiple images as a minimum value among the computed differences over a selected range. The steps are repeated one or more times to obtain a sequence of estimated blur width values. A focus position is adjusted based on the sequence of estimated blur width values.

[12] F. Albu, ”Registration of differently scaled images”, US 8,493,460, July 23, 2013

www.google.com/patents/US8493460

ABSTRACT: An image registration method involves computing horizontal and vertical integral projection vectors for first and second distorted or partially distorted images. The images are registered by applying a scale factor estimation between the first and second images on the horizontal and vertical integral projection vectors

[11] F. Albu, ”Registration of distorted images”, US 8,493,459, July 23, 2013

www.google.com/patents/US8493459

ABSTRACT: An image registration method involves computing horizontal and vertical integral projection vectors for first and second distorted or partially distorted images or distortion-corrected images, or both. The images are registered by applying a translation, rotation and/or scale factor estimation between the first and second images on the horizontal and vertical integral projection vectors.

[10] F. Albu, E. Steinberg, A. Drimbarean, C. Florea, A. Zamfir, P. Corcoran , V. Poenaru,”Image processing method and apparatus”, US 8,417,055, Apr. 9, 2013

www.google.com/patents/US8417055

[9] F. Albu, A. Drimbarean, A. Zamfir, C. Florea, P. Corcoran, ”Adaptive PSF estimation technique using a sharp preview and a blurred image”, US 8,351,726, Jan 8, 2013

www.google.com/patents/US8351726

[8]. F. Albu, A. Drimbarean, C. Florea, A. Zamfir, “Handheld article with movement discrimination”, US 8.212,882, July 3, 2012

www.google.com/patents/US8212882

ABSTRACT: A digital camera 10 has a pair of angular rate-sensing gyroscopic sensors 130with mutually perpendicular axes and an electronic circuit 120 responsive to the sensor output signals to discriminate between voluntary and involuntary movements of the article as a function of the number of zero crossings per unit time of the signal and the average of the absolute amplitude of the signal.

[7] F. Albu, A. Drimbarean, A. Zamfir, C. Florea, P. Corcoran, ”Adaptive PSF estimation technique using a sharp preview and a blurred image”, US 8,208, 746, June 26, 2012

www.google.com/patents/US8208746

ABSTRACT: An adaptive motion estimation and deblurring technique for acquired digital images includes acquiring multiple digital images with a moving digital image acquisition device that includes an image sensor, including a relatively sharp, underexposed reference image and a blurred image. And initial approximate point spread function (PSF) is estimated corresponding to the moving of the device. A different DC offset point is determined and a second PSF is calculated based on the different DC offset point

[6] F. Albu, A. Drimbarean, A. Zamfir, C. Florea, P. Corcoran, ”Adaptive PSF estimation technique using a sharp preview and a blurred image”, US 8,204, 330, June 19, 2012

www.google.com/patents/US8204330

[5] A. Drimbarean, A. Zamfir, F. Albu, V. Poenaru, C. Florea, P. Bigioi, E. Steinberg, P. Corcoran, ”Low-light video frame enhancement”, US 8,199,222, June 12, 2012

www.google.com/patents/US8199222

ABSTRACT: A method of combining image data from multiple frames to enhance one or more parameters of video image quality includes acquiring a first image at a first exposure duration, as well as acquiring a second image at a second exposure duration shorter than the first exposure duration and at a time just before, just after or overlapping in time with acquiring the first image, such that the first and second images include approximately a same first scene. In this way, the second image is relatively sharp and under-exposed, while the first image is relatively well-exposed and less sharp than the second image. Brightness and/or color information are extracted from the first image and applied to the second image to generate an enhanced version of the second image.

[4] F. Albu, A. Drimbarean, A. Zamfir, C. Florea, ”Image processing method and apparatus”, US 8,155,468, Apr. 10, 2012

www.google.com/patents/US8155468

ABSTRACT: A method of processing an image includes traversing pixels of an image in a single pass over the image. An inverting function is applied to the pixels. A recursive filter is applied to the inverted pixel values. The filter has parameters which are derived from previously traversed pixel values of the image. A pixel value is combined with a filter parameter for the pixel to provide a processed pixel value for a processed image.

[3] F. Albu, A. Drimbarean, A. Zamfir, C. Florea, “Image processing method and apparatus”, US 7,995,855, Aug. 9, 2011

www.google.com/patents/US7995855

[2] F. Albu, P. Corcoran , A. Drimbarean, C. Florea, V. Poenaru, E. Steinberg, A. Zamfir, ”Image processing method and apparatus”, EP2160715 B1, Jan 12, 2011

http://www.google.ca/patents/EP2160715B1

ABSTRACT: An image processing apparatus is arranged to process a first relatively underexposed and sharp image of a scene, and a second relatively well exposed and blurred image, nominally of the same scene, the first and second images being derived from respective image sources. The apparatus provides a portion of the relatively first underexposed image as an input signal to an adaptive filter; and a corresponding portion of the second relatively well exposed image as a desired signal to the adaptive filter. The adaptive filter produces an output signal from the input signal and the desired signal; and an image generator constructs a first filtered image from the output signal, relatively less blurred than the second image.

[1]C. Florea, F. Albu, A. Zamfir, A. Drimbarean, “Handheld article with movement discrimination”, US 7,773,118, Aug. 10, 2010

www.google.com/patents/US7773118

ABSTRACT: A digital camera has a pair of angular rate-sensing gyroscopic sensors with mutually perpendicular axes and an electronic circuit responsive to the sensor output signals to discriminate between voluntary and involuntary movements of the article as a function of the number of zero crossings per unit time of the signal and the average of the absolute amplitude of the signal.