Abstract: A target-pixel-setting section (31) sets a target pixel in a target image to be predicted. A motion-direction-detecting section (32) detects a motion direction corresponding to the target pixel. A pixel-value-extracting section (36) extracts from peripheral images corresponding to the target image, in order to extract a main term that mainly contains component of the target pixel in a moving object that encounters a motion blur in the peripheral images, at least pixel values of pixels in the peripheral images whose space position roughly agree with space position of the target pixel. A processing-coefficient-setting section (37a) sets a specific motion-blur-removing-processing coefficient.

Abstract: An image processing device, method, recording medium, and program where the device includes an image data continuity detector configured to detect continuity of image data made up of a plurality of pixels acquired by real world light signals being cast upon a plurality of detecting elements, and a real world estimating unit configured to estimate real world light signals by approximating image data with discontinuous functions.

Abstract: An imaging apparatus includes: an imaging section configured to approximate one of color matching functions representing sensitivity of the human eye to color by a spectral sensitivity that is obtained as a difference in output between, from among mutually adjacent photoelectric conversion elements, the photoelectric conversion elements arranged at predetermined positions, the imaging section having the photoelectric conversion elements arranged at the predetermined positions; and a signal processing section configured to apply to an output of the imaging section signal processing for converting an output of a photoelectric conversion element into a signal of a color image.

Abstract: A signal processing device, signal processing method, and program and recording medium, whereby images and the like closer approximating real world signals can be obtained. The signal processing device includes a processing region setting unit, a movement vector setting unit, and a real world estimating unit.

Abstract: An image processing device, method, recording medium, and program and a learning device, where the learning device includes a computer configured to compute image data corresponding to light signals when the light signals corresponding to second image data pass through an optical low-pass filter and to output computed image data as first image data, a first tap extractor configured to extract a plurality of pixels corresponding to pixels of interest within the second image data from the first image data, and a learning unit configured to teach a predictor configured to predict pixel values of the pixels of interest from the pixel values of the plurality of pixels extracted by the first tap extractor.

Abstract: A signal processing device, signal processing method, and program and recording medium, whereby images and the like closer approximating real world signals can be obtained. The signal processing device includes a movement vector setting unit and a real world estimating unit.

Abstract: A shooting-information-detecting section detects shooting information from an image pick-up section. A motion-detecting section detects a motion direction of an image on an overall screen based on a motion direction of the image pick-up section contained in the shooting information. A processing-region-setting section sets a processing region in at least any one of a predicted target image and a peripheral image thereof, which correspond to a target pixel in the predicted target image. A processing-coefficient-setting section sets a motion-blur-removing-processing coefficient that corresponds to the motion direction detected in the motion-detecting section. A pixel-value-generating section generates a pixel value that corresponds to the target pixel based on a pixel value of a pixel in the processing region set in the processing-region-setting section and the processing coefficient set in the processing-coefficient-setting section. Motion-blur-removing processing can be accurately performed.

Abstract: A signal processing device, signal processing method, and program and recording medium whereby images and the like closer approximating real world signals can be obtained. The signal processing device includes a movement vector setting unit, a model generator, an equation generator, and a real world waveform estimating unit.

Abstract: An image processing device and method, where the device includes a data continuity detector configured to detect data continuity of image data made up of a plurality of pixels acquired by light signals of a real world being cast upon a plurality of detecting elements each having spatio-temporal integration effects, and a real world estimating unit configured to generate a gradient of pixel values of the plurality of pixels corresponding to a position in one dimensional direction of spatio-temporal directions as to pixels of interest within the image data.

Abstract: An image processing device for processing images of background images and moving objects. A region specifying unit specifies a mixed region made up of a mixture of a foreground object component and a background object component, and a non-mixed region made up of one or the other of a foreground object component and a background object component, and outputs region information corresponding to the specifying results. A foreground/background separation unit separates the input image into foreground component images and background component images, corresponding to the region information. A separated image processing unit processes the foreground component images and background component images individually, corresponding to the results of separation.

Abstract: A motion-vector-setting section (31) sets a first motion vector in units of pixel in a target image. An exposure-time-ratio-setting section (32) sets in units of image an exposure time ratio that is a ratio between a time interval of the target image and a period of exposure time. A motion-blur-amount-setting section (33) sets a motion blur amount in units of pixel based on the exposure time ratio and the first motion vector. Based on the motion amount, a processing-region-setting section (36) sets processing regions as well as a processing-coefficient-setting section (37) sets processing coefficients. A pixel-value-generating section (38) generates pixel values that correspond to the target pixel from pixel values in the processing region and the processing coefficients. A motion-blur-adding section (41) adds a motion blur to an image containing the pixel value generated based on an input second motion vector and the first motion vector.

Abstract: A coefficient learning apparatus includes a regression coefficient calculation unit configured to obtain a tap from an image of a first signal; a regression prediction value calculation unit configured to perform a regression prediction computation; a discrimination information assigning unit configured to assign discrimination information to the pixel of interest; a discrimination coefficient calculation unit configured to obtain a tap from the image of the first signal; a discrimination prediction value calculation unit configured to perform a discrimination prediction computation; and a classification unit configured to classify each of the pixels of the image of the first signal into one of the first discrimination class and the second discrimination class.

Abstract: An image processing apparatus includes a storage unit in which regression coefficient data is stored for each class on the basis of a tap in which a linear feature amount corresponding to a pixel of interest of first image data and a non-linear feature amount determined from the image data are used as elements; a classification unit configured to classify each of linear feature amounts of a plurality of items of input data of the input first image into a predetermined class; a reading unit configured to read the regression coefficient data; and a data generation unit configured to generate data of a second image obtained by making the first image have higher quality by performing a product-sum computation process by using the regression coefficient data read from the reading unit and elements of the tap of each of the plurality of items of input data of the input first image.

Abstract: The present invention makes it possible to process at high speed the foreground component image and the background component image of picked up images on a network platform. A client computer 27 outputs information specifying image data desired to separate to a separation server 11. The separation server 11 obtains the specified image data from a storage server 18 and outputs it to a motion detecting server 12 to perform motion detection processing. Thereafter, the image data, motion vector and positional information are output to an area specifying server 13. The area specifying server 13 generates area information of the image data and outputs the area information to a mixture ratio calculating server 14 in addition to the image data, the motion vector and the positional information.

Abstract: An image processing device, method, and program capable of obtaining processing results which are even more accurate and even more precise as to events in the real world by taking into consideration the real world where data has been acquired. The image processing device may include a computer configured to calculate a product-sum coefficient and a recorder configured to record the product-sum coefficient. The image processing device may also include a data continuity detector, a recorder, and a real world estimating unit.

Abstract: An image processing device, method, and a program capable of obtaining processing results which are even more accurate and even more precise as to events in the real world, taking into consideration the real world where data has been acquired. The image processing device may include a computer configured to compute a product-sum coefficient and a recorder configured to record the product-sum coefficient. In another embodiment, the image processing device may include a data continuity detector, a recorder, and a pixel extractor.

Abstract: An apparatus and method which takes into consideration the real world where data was acquired, and enables obtaining of processing results which are more accurate and more precise as to phenomena in the real world. A data continuity detecting unit detects the continuity of data of second signals, having second dimensions that are fewer than first dimensions had by first signals which are real world signals and are projected whereby a part of the continuity of the real world signals is lost, wherein the continuity to be detected corresponds to the continuity of the real world signals that has been lost. An actual world estimating unit estimates a real world image by estimating the continuity of the real world image that has been lost, based on the continuity of the data detected by the data continuity detecting unit.

Abstract: A signal processing device and signal processing method, and program and recording medium, whereby images and the like closer approximating real world signals can be obtained. An actual world estimating unit estimates the actual world function, assuming that the pixel value of each pixel corresponding to a position in the x direction of image data wherein real world light signals are projected on a plurality of pixels each having the time-space integration effects, and part of the continuity of the real world light signals has been lost is a pixel value acquired by integrating the actual world function corresponding to the real world light signals approximated with a spline function in the x direction. An image generating unit generates an image by integrating the actual world function in the x direction in predetermined increments.

Abstract: The present invention enables the high speed processing of a foreground component image and a background component image associated with images received on a network platform. A client computer outputs information specifying image data to a separation server. The separation server then obtains the specified image data from a storage server and outputs it to a motion detecting server to perform motion detection processing. Thereafter, the image data, a motion vector, and positional information are output to an area specifying server. The area specifying server generates area information corresponding to the image data and outputs the area information to a mixture ratio calculating server in addition to the image data, the motion vector, and the positional information.

Abstract: An apparatus for detecting a mixed area in frames. An object extracting unit extracts a foreground object from an input image and generates an area-specified object formed of the foreground object and a value indicating that the foreground object belongs to a background area. A motion compensator compensates for the motion of the area-specified object based on a motion vector and positional information thereof. A subtracting unit subtracts the pixel value of a pixel belonging to a foreground object of a current frame from the corresponding pixel of the foreground object of a preceding frame, so as to obtain a frame difference between the pixels belonging to the foreground area. A threshold-value processor detects a mixed area based on the difference.