An image processor performs a histogram acquisition step of acquiring a histogram representing a distribution of gradation values of pixels in a fundus color image captured by irradiating a fundus with a plurality of beams of single-color light having different wavelengths, the histogram being acquired for each channel corresponding to each beam of single-color light, a histogram correction step of acquiring a corrected histogram by correcting the histogram of each channel acquired in the histogram acquisition step, of which a target pattern is set for each channel in advance, so as to fit to the corresponding target pattern, and a color tone corrected image generation step of generating a color tone corrected image, in which a distribution of gradation values for each channel is represented by the corrected histogram, based on the corrected histogram of each channel.

A dual sensor imaging system and a depth map calculation method thereof are provided. The dual sensor imaging system includes at least one color sensor, at least one infrared ray (IR) sensor, a storage device, and a processor. The processor is configured to load and execute a computer program stored in the storage device to: control the color sensor and the IR sensor to respectively capture multiple color images and multiple IR images by adopting multiple exposure conditions suitable for an imaging scene, adaptively select a combination of the color image and the IR image that are comparable to each other from the color images and the IR images; and calculate a depth map of the imaging scene by using the selected color image and IR image.

A dual sensor imaging system and a depth map calculation method thereof are provided. The dual sensor imaging system includes at least one color sensor, at least one infrared ray (IR) sensor, a storage device, and a processor. The processor is configured to load and execute a computer program stored in the storage device to: control the color sensor and the IR sensor to respectively capture multiple color images and multiple IR images by adopting multiple exposure conditions suitable for an imaging scene, adaptively select a combination of the color image and the IR image that are comparable to each other from the color images and the IR images; and calculate a depth map of the imaging scene by using the selected color image and IR image.

One embodiment provides a method comprising generating, via an edge detection algorithm, a first edge map based on a first frame of an input content comprising a sequence of frames. The method further comprises generating, via the edge detection algorithm, a second edge map based on a second frame of the input content. The first frame precedes the second frame in the sequence of frames. The method further comprises determining a difference between the first edge map and the second edge map, determining a metric indicative of an estimated amount of judder present in the input content based on the difference, and dynamically adjusting a frame rate of the input content based on the metric. The input content is displayed on a display device at the adjusted frame rate.

One embodiment provides a method comprising generating, via an edge detection algorithm, a first edge map based on a first frame of an input content comprising a sequence of frames. The method further comprises generating, via the edge detection algorithm, a second edge map based on a second frame of the input content. The first frame precedes the second frame in the sequence of frames. The method further comprises determining a difference between the first edge map and the second edge map, determining a metric indicative of an estimated amount of judder present in the input content based on the difference, and dynamically adjusting a frame rate of the input content based on the metric. The input content is displayed on a display device at the adjusted frame rate.

When performing anisotropic filtering when sampling a texture in a graphics processing system, a number of positions for which to sample the texture along an anisotropy direction is determined. When the determined number of positions for which to sample the texture along the anisotropy direction is a non-integer value that exceeds a lower integer value by more than a threshold amount, samples are taken along the anisotropy direction in the texture for a number of positions corresponding to the next higher multiple of 2 to the determined non-integer number of positions to be sampled. When the determined number of positions for which to sample the texture along the anisotropy direction does not exceed the lower integer value by at least the threshold amount, samples are taken along the anisotropy direction in the texture for a number of positions corresponding to the lower integer value.

When performing anisotropic filtering when sampling a texture in a graphics processing system, a number of positions for which to sample the texture along an anisotropy direction is determined. When the determined number of positions for which to sample the texture along the anisotropy direction is a non-integer value that exceeds a lower integer value by more than a threshold amount, samples are taken along the anisotropy direction in the texture for a number of positions corresponding to the next higher multiple of 2 to the determined non-integer number of positions to be sampled. When the determined number of positions for which to sample the texture along the anisotropy direction does not exceed the lower integer value by at least the threshold amount, samples are taken along the anisotropy direction in the texture for a number of positions corresponding to the lower integer value.

A signal processing apparatus that can suppress degradation of accuracy of phase difference detection. An obtaining unit obtains a plurality of frames of image signals from a plurality of photoelectric conversion units, which receives light fluxes with different incident directions from an object, an information receiving unit receives saturation information indicating whether the obtained image signals are saturated, a filter arithmetic unit subjects the output image signals of the plurality of frames to filter processing, an evaluation value calculation unit calculates a multivalued saturation evaluation value indicating reliability of the image signals subjected to the filter processing using the saturation information of the image signals of the frames most recently output, and a phase difference detection unit determines whether to use the image signals subjected to the filter processing for phase difference detection based on the calculated saturation evaluation value.

A signal processing apparatus that can suppress degradation of accuracy of phase difference detection. An obtaining unit obtains a plurality of frames of image signals from a plurality of photoelectric conversion units, which receives light fluxes with different incident directions from an object, an information receiving unit receives saturation information indicating whether the obtained image signals are saturated, a filter arithmetic unit subjects the output image signals of the plurality of frames to filter processing, an evaluation value calculation unit calculates a multivalued saturation evaluation value indicating reliability of the image signals subjected to the filter processing using the saturation information of the image signals of the frames most recently output, and a phase difference detection unit determines whether to use the image signals subjected to the filter processing for phase difference detection based on the calculated saturation evaluation value.

A method of processing a given region of interest (ROI) of an X-ray image of a person's breast to determine presence of a malignancy, the X-ray image having X-ray pixels that indicate intensity of X-rays that passed through the breast to generate the image, the method comprising: for each given X-ray pixel in the given ROI and each of a selection of J(r) X-ray pixels at respective pixel radii PR(r), 1≤r≤R, from the given x-ray pixel, determining a binary number that provides a measure X-ray intensity indicated by the selected X-ray pixel relative to X-ray intensity indicated by the given X-ray pixel; using the determined binary numbers for the selected X-ray pixels at each pixel radius PR(r) to determine a decimal number for the pixel radius PR(r); histogramming the frequency of occurrence of values of the determined decimal numbers as a function of pixel radius for the given X-ray pixels in the given ROI; determining a texture feature vector, for the given ROI having components that are equal to the frequencies of occurrence for a selection of M histogrammed values; and processing the histogrammed frequencies of occurrence for the M values to determine whether the given ROI is malignant.