In one embodiment, a computer-based method includes obtaining a first image where the first image includes one or more patterns, generating a second image that substantially removes or reduces the one or more patterns from the first image at least partially by automatically detecting the one or more patterns and a zone where the one or more patterns occur in the first image, converting the first image to frequency domain data, applying a multi-parameter filter to the frequency domain data to substantially remove or reduce the one or more patterns. The parameters may include bandwidths in a depth and azimuthal direction. The parameters may be adapted in the multi-parameter filter based on the one or more patterns. The method also includes transforming the frequency domain data to spatial domain data and outputting the second image based at least in part on the spatial domain data.

An object information obtaining device includes a light source which emits light, an acoustic wave detecting unit which detects a photoacoustic wave generated by irradiation of an object with the light, and outputs an electric signal in response to detection of the photoacoustic wave, and a processing unit configured to perform two or more types of processing to photoacoustic signal data based on the electric signal to obtain object information corresponding to each of the two or more types of processing, and to display on a display unit the object information corresponding to at least one processing selected by a user out of the two or more types of processing.

A frequency adaptive descreening method includes obtaining a scan image of an original document, dividing a region of the scan image by analyzing frequency characteristics of the obtained scan image, estimating a resolution with respect to each of regions resulting from dividing the region according to the analyzed frequency characteristics, and adaptively performing filtering on the regions resulting from dividing the region by using the estimated resolution.

An example apparatus for compressing dynamic range includes an image receiver to receive an input image with a high dynamic range. The apparatus further includes a darkness gamma transfer calculator to calculate gain values for each output pixel via a darkness gamma transfer function. The apparatus also further includes a gain applicator to apply the gain values to color channel values of the input image to generate a compressed image.

An example apparatus for compressing dynamic range includes an image receiver to receive an input image with a high dynamic range. The apparatus further includes a darkness gamma transfer calculator to calculate gain values for each output pixel via a darkness gamma transfer function. The apparatus also further includes a gain applicator to apply the gain values to color channel values of the input image to generate a compressed image.

Disclosed are a method of acquiring an image using a light-emitting element array and an apparatus therefor. The method of acquiring an image using a light-emitting element array includes reconstructing a first image from some images among source images, detecting a partial region containing a detection target object from the first image, acquiring partial-region images corresponding to the partial region from each of the source images, and reconstructing a second image from the partial-region images using the FPMP.

Described herein is an image processing apparatus (701) comprising one or more processors (704) configured to: receive (601) a plurality of input images (301, 302, 303); for each input image, form (602) a set of decomposed data by decomposing the input image (301, 302, 303) or a filtered version thereof (307, 308, 309) into a plurality of frequency-specific components (313) each representing the occurrence of features of a respective frequency interval in the input image or the filtered version thereof; process (603) each set of decomposed data using one or more convolutional neural networks to form a combined image dataset (327); and subject (604) the combined image dataset (327) to a construction operation that is adapted for image construction from a plurality of frequency-specific components to thereby form an output image (333) representing a combination of the input images. The resulting HDR output image may have fewer artifacts and provide a better quality result. The apparatus is also computationally efficient, having a good balance between accuracy and efficiency.

Described herein is an image processing apparatus (701) comprising one or more processors (704) configured to: receive (601) a plurality of input images (301, 302, 303); for each input image, form (602) a set of decomposed data by decomposing the input image (301, 302, 303) or a filtered version thereof (307, 308, 309) into a plurality of frequency-specific components (313) each representing the occurrence of features of a respective frequency interval in the input image or the filtered version thereof; process (603) each set of decomposed data using one or more convolutional neural networks to form a combined image dataset (327); and subject (604) the combined image dataset (327) to a construction operation that is adapted for image construction from a plurality of frequency-specific components to thereby form an output image (333) representing a combination of the input images. The resulting HDR output image may have fewer artifacts and provide a better quality result. The apparatus is also computationally efficient, having a good balance between accuracy and efficiency.

Apparatuses, systems, and techniques to perform a fast Fourier transform operation. In at least one embodiment, a fast Fourier transform operation is performed based on one or more parameters, wherein the one or more parameters indicate information about one or more operands of the fast Fourier transform.

Apparatuses, systems, and techniques to perform a fast Fourier transform operation. In at least one embodiment, a fast Fourier transform operation is performed based on one or more parameters, wherein the one or more parameters indicate information about one or more operands of the fast Fourier transform.