Abstract:
A method includes determining, by a hardware processor and based on an image frame, a first edge strength distribution on a horizontal edge map and a second edge strength distribution on a vertical edge map. The first and second edge strength distributions are redistributed to narrow at least one of the first and second edge strength distributions. Non-texture regions of pixels are determined based on a data correlation map of the image frame. Edge strength magnitudes for the pixels of the non-texture regions of the horizontal edge map and the vertical edge map are determined. A high resolution frame is generated by adjusting intensity of respective pixels of the non-texture region of the horizontal edge map and the vertical edge map, the adjusting being based on neighboring pixels edge strength magnitudes.
Abstract:
A band processing circuit which generates image signals corresponding to different frequency bands from an image signal in which signals corresponding to different colors are arranged and which suppresses noise by synthesizing the image signals of the different frequency bands, a sampling circuit which generates image signal corresponding to the colors by sampling the image signal input from the band processing circuit in accordance with a predetermined arrangement, and a luminance/color generation circuit which generates a luminance signal in which aliasing is suppressed using an image signal output from the sampling circuit.
Abstract:
A method for applying a filter to data to improve data quality and/or reduce file size. In one example, a region of interest of an image is identified. A histogram is generated of pixel intensity values in the region of interest. The histogram is iteratively updated to focus (zoom) in on the highest peak in the histogram. A Gaussian curve is fitted to the updated histogram. A bilateral filter is applied to the images, where parameters of the bilateral filter are based on the parameters of the Gaussian curve.
Abstract:
To extend the working range of depth from defocus (DFD) particularly on small depth of field (DoF) images, DFD is performed on an image pair at multiple spatial resolutions and the depth estimates are then combined. Specific implementations construct a Gaussian pyramid for each image of an image pair, perform DFD on the corresponding pair of images at each level of the two image pyramids, convert DFD depth scores to physical depth values using calibration curves generated for each level, and combine the depth values from all levels in a coarse-to-fine manner to obtain a final depth map that covers the entire depth range of the scene.
Abstract:
A method and apparatus for determining the volume of a bodily structure including the steps of acquiring at least two ultrasound images, estimating the location of the perimeter of a structure of interest as viewed in cross section in each said ultrasound image, calculating the cross sectional area of such structure as so viewed, and combining the perimeter and area information from the at least two images to calculate the volume of the structure.
Abstract:
A restoration filter based on a point spread function of an optical system is applied to source image data acquired through photographing using the optical system to acquire restored image data (S13: filter application step). Adjustment of an amplification factor of the difference between source image data and restored image data is performed, and recovered image data is acquired from the difference after adjustment and source image data (S15: gain adjustment step). In the filter application step, a common filter determined regardless of a value of a magnification of an optical zoom of the optical system is used as the restoration filter, and in the gain adjustment step, the amplification factor is determined based on the magnification of the optical zoom of the optical system.
Abstract:
Automated systems, methods and tools that automatically extract and select portions of an image to automatically generate a premium finish mask specific to the image which require little or no human intervention are presented. Graphical user interface tools allowing a user to provide an image and to indicate regions of the image for application of premium finish are also presented.
Abstract:
A computer-implemented method and apparatus are described for automatically selecting a region in a blurred image for blur kernel estimation. The method may include accessing a blurred image and defining a size for each of a plurality of regions in the image. Thereafter, metrics for at least two of the plurality of regions are determined, wherein the metrics are based on a number of edge orientations within each region. A region is selected from the plurality of regions based on the determined metrics, and a blur kernel for deblurring the blurred image is then estimated for the selected region. The blurred image is then deblurred using the blur kernel.
Abstract:
Edge enhancement processing is performed for the luminance of each pixel of an image, and the correction value of the pixel after the edge enhancement processing is decided according to the saturation of each pixel of the image. The value of the pixel after the edge enhancement processing is corrected using the decided correction value.
Abstract:
Disclosed are an image processing device, an imaging device, an image processing method, and a program capable of acquiring a moving image with excellent image quality while maintaining continuity of a restoration process between frames even if there is a rapid change of a photographing environment in a moving image. An image processing device includes a restoration control processing unit 36 which subjects a moving image including a plurality of frames acquired by photographing using an optical system to a restoration process based on a point spread function of the optical system to acquire recovered image data. The restoration control processing unit 36 controls the restoration process for a frame to be processed among a plurality of frames based on imaging information of a reference frame including a frame after the frame to be processed in a time series.