Abstract: A radar image processing device includes at least one memory configured to store instructions; and at least one processor configured to execute the instructions to: determine a search range based on a reference block and a layover direction, the reference block being set as an area of interest in a radar image generated from data obtained by an imaging radar, the layover direction being a direction in which layover occurs in the radar image and being estimated from an incident direction of an electromagnetic wave used for observation by the imaging radar; extract a similar block that is similar to the reference block and included in the search range by searching the search range; and perform filtering processing for reducing speckles generated in the radar image by using the reference block and the extracted similar block.

Abstract: An information processing apparatus (10) according to the present disclosure includes: an object recognition unit (11) that outputs, by using a first modal signal and a first modal recognition model corresponding to the first modal signal, an inference result regarding the first modal signal; a training data processing unit (12) that generates first modal training data regarding the first modal signal by using the inference result, and updates second modal training data regarding a second modal signal that is different from the first modal signal by using the first modal training data; and a recognition model update unit (13) that updates a second modal recognition model corresponding to the second modal signal by using the second modal training data.

Abstract: To provide an efficient training process even in a case where training images having a limited variation of shooting angles are available.

Abstract: To provide an efficient and stable training process even in a case where a small amount of target domain labeled data is available.

Abstract: An endoscope device includes a processor configured to calculate light source control information based on first information regarding a scope and second information regarding a light source device, and to control a light source of the light source device based on the light source control information. The second information includes a ratio of an amount of light emitted from a distal end of a reference scope to an amount of light emitted from the light source device to the reference scope.

Abstract: The image processing device 60 includes an image deformation unit 61 which deforms object presence areas in two object presence images, in which one or more objects are present, obtained from each of two observed images to generate two deformed images, based on an observation angle of each of the two observed images and a size of the object appearing in each of the two observed images, and an image generation unit 62 which generates a synthesized image by synthesizing the two deformed images, determines difference of the object between the two object presence images, and generates an image capable of identifying the determined difference.

Abstract: A learning apparatus (500) according to the present invention includes a detection unit (510) that detects, as a candidate region of a learning target, a region detected by one of first detection processing of detecting an object region from a predetermined image and second detection processing of detecting a change region from background image information and the image, and not detected by the other, an output unit (520) that outputs at least a part of the candidate region as a labeling target, and a learning unit (530) that learns a model for performing the first detection processing or a model for performing the second detection processing by using the labeled candidate region as learning data.

Abstract: An object is to provide an image processing apparatus capable of appropriately distinguishing changes in an area that have occurred over a period of time. An image processing apparatus may include: a difference image generator means to generate a difference image from input SAR images; an intensity change feature extractor means to extract an intensity-based change feature from the difference image; a speckle change feature extractor means to extract speckle-based change features from the input SAR images; a combined feature extractor means to combine the intensity change feature and the speckle change feature to generate a complete representation of changes; and a classifier means to classify the pixels in several change classes using the combined feature and output a change map.

Abstract: An information processing apparatus (10) according to the present disclosure includes: an object recognition unit (11) that outputs, by using a first modal signal and a first modal recognition model corresponding to the first modal signal, an inference result regarding the first modal signal; a training data processing unit (12) that generates first modal training data regarding the first modal signal by using the inference result, and updates second modal training data regarding a second modal signal that is different from the first modal signal by using the first modal training data; and a recognition model update unit (13) that updates a second modal recognition model corresponding to the second modal signal by using the second modal training data.

Abstract: An object is to provide an image processing apparatus capable of appropriately detecting changes of a target object. An image processing apparatus may include: object-driven feature extractor means to extract relevant features of target object from input images; a feature merger means to merge the features extracted from the input images into a merged feature; a change classifier means to predict a probability of each change class based on the merged feature; an object classifier means to predict a probability of each object class based on the extracted features of each image; a multi-loss calculator means to calculate a combined loss from a change classification loss and an object classification loss; and a parameter updater means to update the parameters of the object-driven feature extractor means.

Abstract: An image processing device (500) according to the present invention is provided with: a visibility index computation means (501) which, upon receiving two or more images to be merged, computes, for each image to be merged, a visibility index, which is an index relating to the visibility of an object to be viewed in the image, on the basis of a contrast value of the image and the amount of noise included in the image, wherein the two or more images to be merged have different characteristics and have at least an overlap region; a merge ratio computation means (502) which computes an image merge ratio between the images to be merged, on the basis of the computed visibility indices; and an image merging means (503) which merges the images to be merged, on the basis of the computed merge ratio, to generate a merged image.

Abstract: A learning device 10 includes a learning means 11 that, by using learning data including at least a set of image areas representing a periodic change of a predetermined object among changes between a plurality of images and a set of image areas representing a change other than the periodic change among the changes between the plurality of images, causes a detector to learn a process for detecting a change other than the periodic change among the changes between the plurality of images.

Abstract: Provided is to generate learning data set for learning a cloud correction processing method. A device includes: synthesis unit configured to have a more cloud image and a less cloud image including a same observation object as a set, and receive a first thick cloud area indicating a thick cloud in the more cloud image and a second thick cloud area indicating the thick cloud in the less cloud image; execute a first operation for the first and/or second thick cloud area to generate a first mask in the less cloud image; execute a second operation for the first and/or second thick cloud area to generate a second mask in the more cloud image; and adopt, as learning data, the set including data including the generated first mask and the more cloud image and data including the generated second mask and the less cloud image.

Abstract: A radar image processing device includes at least one memory configured to store instructions; and at least one processor configured to execute the instructions to: determine a search range based on a reference block and a layover direction, the reference block being set as an area of interest in a radar image generated from data obtained by an imaging radar, the layover direction being a direction in which layover occurs in the radar image and being estimated from an incident direction of an electromagnetic wave used for observation by the imaging radar; extract a similar block that is similar to the reference block and included in the search range by searching the search range; and perform filtering processing for reducing speckles generated in the radar image by using the reference block and the extracted similar block.

Abstract: An image processing device (500) according to the present invention is provided with: a visibility index computation means (501) which, upon receiving two or more images to be merged, computes, for each image to be merged, a visibility index, which is an index relating to the visibility of an object to be viewed in the image, on the basis of a contrast value of the image and the amount of noise included in the image, wherein the two or more images to be merged have different characteristics and have at least an overlap region; a merge ratio computation means (502) which computes an image merge ratio between the images to be merged, on the basis of the computed visibility indices; and an image merging means (503) which merges the images to be merged, on the basis of the computed merge ratio, to generate a merged image.

Abstract: An image processing device 500 for detecting and correcting areas affected by a cloud in an input image is provided. The image processing device 500 includes: endmember extraction unit 501 that extracts a set of spectra of one or more endmembers from the input image; cloud spectrum acquisition unit 502 that acquires one cloud spectrum in the input image; endmember selection unit 503 that compares the endmember spectra with the cloud spectrum, removes one or more spectra from the set of spectra of the endmember spectra, the one or more spectra being same as or similar to the one cloud spectrum, and outputs a resultant set of spectra as an authentic set of spectra; and an unmixing unit 504 that derives, for each pixel in the input image, one or more fractional abundances of the one or more endmembers and a fractional abundance of cloud in the authentic set of spectra, and detects one or more cloud pixels in the input image.

Abstract: An image processing system includes a storage device, and a processor coupled to the storage device and configured to extract, from an input image, an aerosol spectrum across a plurality of wavelength bands of the input image. The storage device contains therein a database storing a plurality of predetermined aerosol spectra, and a plurality of corresponding values associated with an aerosol optical property at the plurality of wavelength bands. The processor is further configured to retrieve, from the database, values associated with the aerosol optical property at the plurality of wavelength bands, the retrieved values corresponding to the extracted aerosol spectrum. The processor is further configured to correct the input image, by using the retrieved values associated with the aerosol optical property at the plurality of wavelength bands, to generate a corrected image.

Abstract: An image processing system includes a storage device, and a processor coupled to the storage device and configured to extract, from an input image, an aerosol spectrum across a plurality of wavelength bands of the input image. The storage device contains therein a database storing a plurality of predetermined aerosol spectra, and a plurality of corresponding values associated with an aerosol optical property at the plurality of wavelength bands. The processor is further configured to retrieve, from the database, values associated with the aerosol optical property at the plurality of wavelength bands, the retrieved values corresponding to the extracted aerosol spectrum. The processor is further configured to correct the input image, by using the retrieved values associated with the aerosol optical property at the plurality of wavelength bands, to generate a corrected image.

Abstract: The present invention provides an image processing method, an image processing device, and an image processing program which require low computing costs and with which it is possible to minimize noise amplification and halo generation caused by HDR. An image processing device according to one embodiment of the present invention has: a multi-resolution image generation means for generating a multi-resolution image; a correction amount calculation means for calculating a brightness correction amount on the basis of a lowest-resolution image of the multi-resolution image, a differential image between adjacent resolutions of the multi-resolution image, and edge information calculated at each resolution of the multi-resolution image; and a noise suppression means for calculating, on the basis of the lowest-resolution image, the differential image between adjacent resolutions, the edge information, and the brightness correction amount, an image after brightness correction in which a noise component is suppressed.

Abstract: The invention enables image processing of visible light and near-infrared light using an imaging device. An acquisition unit (110) acquires an image signal representing an image including near-infrared light that has an intensity according to a pattern having a prescribed geometric shape. A signal processing unit (120) uses pattern information which defines the pattern to output, a color signal representing visible light components corresponding to the image signal and a near-infrared signal representing near-infrared light components corresponding to the image signal.