Abstract: A method for performing a convergence calculation using a projective transformation between images captured by two cameras to observe a flat part of an object in the images, wherein a computational load is reduced while securing a convergence property of the convergence calculation. Initial values (n0(i), d0(i)) are set to values satisfying a limiting condition that should be satisfied by the initial values (n0(i), d0(i)), where the limiting condition is that a plane ?a(i) defined by the initial values (n0(i), d0(i)) of given types of parameters (n(i), d(i)) of a projective transformation matrix in the convergence calculation is inclined with respect to an actual plane including the flat part of the object to be observed.

Abstract: A robot capable of performing appropriate movement control while reducing arithmetic processing for recognizing the shape of a floor. The robot sets a predetermined landing position of steps of the legs on a present assumed floor, which is a floor represented by floor shape information used for a current motion control of the robot, during movement of the robot. An image projection area is set, and is projected on each image captured by cameras mounted on the robot for each predetermined landing position in the vicinity of each of the predetermined landing positions. Shape parameters representing the shape of an actual floor partial area are estimated, forming an actual floor whose image is captured in each partial image area, based on the image of the partial image area generated by projecting the set image projection area on the images captured by the cameras for each partial image area.

Abstract: A method is provided for speeding up a super-resolution processing by reducing the number of times for convolution operation that is the number of times for estimation calculation. A fast method of super-resolution processing for speeding up a super-resolution processing that estimates a high-resolution image from multiple low-resolution images with a displacement, which comprising: a first step for performing a registration of said multiple low-resolution images in a high-resolution image space and treating all pixels of said multiple low-resolution images after the registration as pixels sampled at unequal interval within said high-resolution image space; a second step for dividing said high-resolution image space into multiple small areas with a predefined size; and a third step for defining an estimated value at a predefined representative position within said small area as an estimated value of all pixels that exist within said small area for each small area divided in said second step.

Abstract: An optical system, imaging device and high-resolution processing method precisely generate a high-resolution image by using image data with few pixels. The optical system images an optical image in an imaging unit, the imaged image is spatially discretized so as to be sampled and converted into an image signal, thereby being recorded in a recording unit. A timing at which the image is imaged by the imaging unit is recorded in an imaging timing recording unit. A weight coefficient for the image is calculated by a weight calculating unit by utilizing the timing information obtained by the imaging timing recording unit. A high-resolution processing unit generates a high-resolution image by using the weighted information of the image generated by the weight calculating unit.

Abstract: A motion calculation device includes an image-capturing unit configured to capture an image of a range including a plane and outputs the captured image, an extraction unit configured to extract a region of the plane from the image, a detection unit configured to detect feature points and motion vectors of the feature points from a plurality of images captured by the image-capturing unit at a predetermined time interval; and a calculation unit configured to calculate the motion of the host device based on both of an epipolar constraint relating to the feature points and a homography relating to the region.

Abstract: [Problem]An object of the present invention is to provide an image registration processing apparatus that is capable of performing a robust and high-accuracy registration processing with respect to an entire image between images including multiple motions.

Abstract: The present invention provides a signal readout method of solid-state imaging device which can simultaneously readouts the signals having different properties that can generate multiple images obtained by capturing the same subject under different capturing conditions from one solid-state imaging device. A signal readout method of solid-state imaging device that is applied to a solid-state imaging device with a color filter array (CFA) and multiple pixels, the method characterized in that a pixel mixture of a different number of pixels is performed for every readout signal in the solid-state imaging device, and a signal after the pixel mixture is readout.

Abstract: The pixel mixture method of the present invention for mixing several pixels on a solid-state image sensing device, which is applied to an imaging device having the solid-state image sensing device with a color filter array (CFA) and multiple pixels, comprising: a pixel mixture operating step for performing a pixel mixture operation based on a pixel mixture operation equation for the several pixels that are adjacent spatially; a color conversion matrix generating step for generating a color conversion matrix based on the kind of colors of a color space after mixture and the pixel mixture operation equation; and a desired color space converting step for converting the color space after mixture into a desired color space based on the generated color conversion matrix.

Abstract: The invention provides imaging device and high-resolution processing method of image which precisely generate high-resolution image by using image data with a little number of the pixels. An optical system images an optical image in an imaging unit (101), the imaged image is spatially discretized so as to sampled and converted into an image signal, thereby being recorded in a recording unit (105). Further, a timing at which the image is imaged by the imaging unit (101) is recorded in an imaging timing recording unit (107). A weight coefficient for imaged image is calculated by a weight calculating unit (104) by utilizing the timing information obtained by the imaging timing recording unit (107). A high-resolution processing unit (106) generates a high-resolution image by using the weighted information of the image generated by the weight calculating unit (104).

Abstract: Disclosed is an image processing apparatus that is capable of effectively generating a high-resolution image with high image quality from multiple low-resolution images having displacements by an iterative reconstruction processing based on a reconstruction-based super-resolution processing method.

Abstract: An image processing method includes: a frame selection step; a motion vector calculation step for calculating a motion vector value from one frame image to another frame image by tracking each pixel of one or a plurality of frame images; and a motion vector correction step for calculating an imaginary motion vector when a motion vector that can be tracked to a tracking destination pixel corresponding to a pixel tracked up to a midway point does not exist due to an encoding type of a block including the pixel tracked up to the midway point.

Abstract: An image processing method includes: a frame selection step for selecting a base frame and a reference frame; an image displacement amount calculation step for calculating an image displacement amount between the reference frame and the base frame; a weighting coefficient generation step for generating a weighting coefficient using at least one of an encoding type of the reference frame and the motion information of the encoded moving image data; and an image quality improvement step for improving an image quality of the base frame using the image displacement amount calculated in the image displacement amount calculation step and the weighting coefficient generated in the weighting coefficient generation step.

Abstract: The present invention provides an image quality improvement processing method corresponding to multiple regions that performs the image quality improvement processing so as to be capable of simultaneously displaying multiple regions of interest that image quality is improved and the entire basis image without generating unnatural edges in boundaries between regions of interest even in the case that multiple regions of interest are set in the basis image.

Abstract: The present invention provides a method for generating a high-resolution virtual-focal-plane image which is capable of generating a virtual-focal-plane image with an arbitrary desired resolution simply and rapidly by using multi-view images.

Abstract: The present invention provides a three-dimensional surface generation method that directly and efficiently generates a three-dimensional surface of the object surface from multiple images capturing a target object. The three-dimensional surface generation method of the present invention sets one image as a basis image from multiple images obtained by capturing the target object from different viewpoint positions and sets other images as reference images, and then generates two-dimensional triangle meshes on the basis image.

Abstract: The present invention provides an image quality improvement processing apparatus that removes occlusion regions and regions that the registration error is large, selects pixels suitable for the image quality improvement processing, and generates an image with high image quality.

Abstract: The present invention provides a high-resolution image generation method which is capable of generating a high-resolution image from multiple low-resolution images having displacements without using an iterative computation. A high-resolution image generation method for generating a high-resolution image from multiple low-resolution images having displacements, comprises a first step of performing a registration processing of multiple low-resolution images; a second step of generating an average image having the undefined pixels and a weighted image based on the displacement information obtained by the registration processing and multiple low-resolution images; and a third step of generating the high-resolution image by estimating pixel values of the undefined pixels included in the average image.

Abstract: In consideration of N-dimensional similarity, a multiparameter high precision concurrent estimation method and a multiparameter high precision concurrent estimation program in image subpixel matching, which can estimate a correspondence parameter between images precisely, concurrently, and stably with a small amount of computation at high speed.

Abstract: The present invention provides a region-selection-based image registration method for estimating motions between an image of interest in an image sequence and a reference image in the image sequence which can be applied to the registration of the object having every geometry and by which the high-precision image registration with robustness to illumination variation and occlusion can be conducted. An image registration method for conducting a high-precision image registration between a reference image in an image sequence capturing an object and an image of interest in said image sequence, the method characterized in that a predetermined region on the reference image is set as a region of interest, when conducting the high-precision image registration, a motion parameter is estimated based on pixels of a mask image representing a region where the registration is performed precisely by a predetermined transformation within the region of interest that is set.

Abstract: An image processing apparatus according to the present invention includes an image acquisition section acquiring a multiple overlapping image in which a subject image is multiplexed, a filtering section filtering the multiple overlapping image acquired by the image acquisition section, a similarity calculation section calculating similarity between overlapping images contained in the multiple overlapping image filtered by the filtering section, and an overlapping image displacement calculation section using the similarity obtained by the similarity calculation section to calculate overlapping image displacement in the multiple overlapping image.