Abstract: The imaging device (10) includes an optical element (12) having each transparent substrate and a plurality of structures disposed on or in the transparent substrate in a plane direction of the transparent substrate, an imaging element (11) in which a plurality of pixels including a photoelectric conversion elements are disposed, and a signal processing unit (13) configured to generate an image signal based on an electrical signal acquired from the imaging element (11), wherein the optical element (12) forms an image in which a point spread function of each wavelength is convoluted on a plurality of pixels corresponding to each polarized light component depending on polarized light components by outputting light in a state in which the optical element has different point spread functions for respective wavelengths, the plurality of structures have the same height in a side view, and the signal processing unit (13) reconstructs an image in which a point spread function of each wavelength is convoluted for each

Abstract: An imaging device includes an optical element including a transparent substrate and a plurality of structures disposed on or in the transparent substrate in a plane direction of the transparent substrate, an imaging sensor in which a plurality of pixels each including a photoelectric conversion element are arranged, and a signal processing unit configured to generate an image signal based on an electric signal obtained from the imaging sensor, wherein the optical element outputs light with a different point spread function for each wavelength to form, on the imaging sensor, an image in which the point spread function of each wavelength is convoluted, the plurality of structures have the same height in a side view, and the signal processing unit reconstructs an image in which the point spread function of each wavelength is convoluted.

Abstract: A reference specifying unit specifies reference values corresponding to a plurality of points of point cloud data. A residual decoding unit decodes attribute residuals of the plurality of points from encoded residual data obtained by encoding the attribute residuals, the attribute residuals of the plurality of points being residuals of attribute values of the plurality of points with respect to the reference values. An attribute value calculation unit calculates, for each of the plurality of points, an attribute value of the point from an attribute residual and a reference value.

Abstract: A decoding method is a decoding method performed by a decoding device, the decoding method including steps of: acquiring, from among a plurality of slice numbers indicating a plurality of slices associated with encoded data of the entire point cloud distributed in a three-dimensional space, a first slice number indicating a first slice associated with encoded data of a point cloud of a first space that is a portion of the three-dimensional space, on the basis of a pointer indicating the first slice; and acquiring the encoded data of the point cloud of the first space on the basis of the first slice number, and decoding point cloud data of the first space from the encoded data of the point cloud of the first space.

Abstract: An image encoding method is an image encoding method executed by an image encoding device, the method including: a feature map generating step of generating a first feature map representing a feature of an encoding target image which is an encoding target image and a second feature map representing a feature of the encoding target image at different resolutions; a correlation map generation step of generating a correlation map representing a correlation distribution between the first and second feature maps; a contraction function generation step of generating a contraction function which is a function used for a contraction process for a predetermined image in a decoding process based on the correlation map; and an encoding step of executing an encoding process on the contraction function and outputting a result of the encoding process.

Abstract: An aspect of the present invention is a learning method for learning a model which reconstructs data and acquires reconstructed data, the learning method includes a plurality of stages, and the learning method includes first sub-processing which is based on an iterative calculation algorithm in which a Lagrange multiplier is not used, second sub-processing which is based on an iterative calculation algorithm in which the Lagrange multiplier is used, and weighting sub-processing which determines processing in each of the plurality of stages based on a weight for determining usage of the first sub-processing and the second sub-processing in each stage.

Abstract: A coding amount estimation device includes: a feature vector generation unit that generates a feature vector on the basis of a feature map generated by an estimation target image and at least one filter set in advance; and a coding amount evaluation unit that evaluates a coding amount of the estimation target image on the basis of the feature vector.

Abstract: An image coding method includes: an image acquisition step of acquiring a coding-target image; a feature map generation step of generating a feature map, based on the image; a contraction function generation step of performing fractal compression of the feature map and generating a contraction function; and an entropy encoding step of performing entropy encoding of the contraction function.

Abstract: An image processing device that updates a pixel value of a processing target image and generates a new image generates a first feature vector based on the processing target image and a first feature map generated with at least one pre-decided filter; updates the processing target image to generate an updated image; generates a second feature vector based on the updated image and a second feature map generated with at least one pre-decided filter; performs quality evaluation of the updated image based on the first and second feature vectors and generates a quality feedback vector which is a vector based on a result of the quality evaluation; performs an encoding amount evaluation on the updated image and generates an encoding amount feedback vector which is a vector based on a result of the encoding amount evaluation; and determines an updating amount in updating of the updated image based on the quality feedback vector and the encoding amount feedback vector.

Abstract: Provided is a signal reconstruction method executed by a signal reconstruction apparatus including a processor and a memory that stores a codec. The signal reconstruction method includes reconstructing an input signal according to a desired purpose, and in the reconstructing, a likelihood of the input signal being a predetermined type of signal is considered by executing coding on a processing result of the input signal, based on the codec previously determined according to a type of the input signal.

Abstract: A predictive image acquisition device is a predictive image acquisition device for associating an observation signal, the observation signal being a signal obtained from an original image serving as a decoding target image and being a lower dimensional signal than the original image, a first predictive image having a high correlation with the original image, and a second predictive image having a high correlation with the original image with each other to obtain a combined predictive image, and includes an interpolation factor acquisition unit configured to obtain an interpolation factor set for each pixel of the combined predictive image from the first predictive image, the second predictive image, and the observation signal, and a combined predictive image acquisition unit configured to combine the first predictive image and the second predictive image for each pixel using the interpolation factor to obtain the combined predictive image, and the pixels constituting the observation signal are expressed by a

Abstract: An image encoding method that generates and encodes a gram matrix representing an image feature when encoding an image to be encoded includes a feature map generation step of generating a plurality of feature maps from the image to be encoded; a gram matrix generation step of generating a gram matrix through calculations between/among the feature maps; a representative vector determination step of generating a representative vector and a representative coefficient value by singular value decomposition of the gram matrix; and a vector encoding step of encoding the representative coefficient value and the representative vector.

Abstract: An image encoding method that expresses an image using pixels or blocks, and colors assigned to the pixels or the blocks when encoding an image to be encoded, and encodes a block division tree and color information, the color information being assigned to all nodes including a root node, branch nodes, and leaf nodes of the block division tree, the method includes: a division tree generation step of dividing the image to be encoded using an arbitrary division tree and thereby generating the block division tree; a color information determination step of determining representative colors that represent interim blocks or final blocks and assigning the determined colors as color information corresponding to the respective nodes, the interim blocks or the final blocks corresponding to the nodes of the block division tree; a tree encoding step of encoding the block division tree; and a color information encoding step of encoding the color information.

Abstract: A predictive image acquisition device is a predictive image acquisition device for associating an observation signal, the observation signal being a signal obtained from an original image serving as a decoding target image and being a lower dimensional signal than the original image, a first predictive image having a high correlation with the original image, and a second predictive image having a high correlation with the original image with each other to obtain a combined predictive image, and includes an interpolation factor acquisition unit configured to obtain an interpolation factor set for each pixel of the combined predictive image from the first predictive image, the second predictive image, and the observation signal, and a combined predictive image acquisition unit configured to combine the first predictive image and the second predictive image for each pixel using the interpolation factor to obtain the combined predictive image, and the pixels constituting the observation signal are expressed by a

Abstract: An image processing device that updates a pixel value of a processing target image and generates a new image generates a first feature vector based on the processing target image and a first feature map generated with at least one pre-decided filter; updates the processing target image to generate an updated image; generates a second feature vector based on the updated image and a second feature map generated with at least one pre-decided filter; performs quality evaluation of the updated image based on the first and second feature vectors and generates a quality feedback vector which is a vector based on a result of the quality evaluation; performs an encoding amount evaluation on the updated image and generates an encoding amount feedback vector which is a vector based on a result of the encoding amount evaluation; and determines an updating amount in updating of the updated image based on the quality feedback vector and the encoding amount feedback vector.

Abstract: A coding amount estimation device includes: a feature vector generation unit that generates a feature vector on the basis of a feature map generated by an estimation target image and at least one filter set in advance; and a coding amount evaluation unit that evaluates a coding amount of the estimation target image on the basis of the feature vector.

Abstract: A video encoding apparatus that predictive-encodes an encoding target image included in an encoding target video. The apparatus includes a prediction device that predicts the encoding target image with reference to a previously-encoded picture as a reference picture and determines first reference information which indicates a first reference region as a reference destination; a second reference information determination device that determines, from reference information used when the first reference region was predictive-encoded, second reference information which indicates a second reference region as another reference destination for the encoding target image; and a predicted image generation device that generates a predicted image based on the second reference information, or both the first reference information and the second reference information.

Abstract: A moving image encoding/decoding apparatus that performs encoding/decoding while predicting a multiview moving image including moving images of a plurality of different views includes: a corresponding region setting unit that sets a corresponding region on a depth map for an encoding/decoding target region; a region dividing unit that sets a prediction region that is one of regions obtained by dividing the encoding/decoding target region; a disparity vector generation unit that generates, for the prediction region, a disparity vector for a reference view using depth information for a region within the corresponding region that corresponds to the prediction region; a motion information generation unit that generates motion information in the prediction region from the reference view motion information based on the disparity vector for the reference view; and a prediction image generation unit that generates a prediction image for the prediction region using the motion information in the prediction region.