The image exposure device includes an image display device that has a plurality of pixels and radiates light according to a display image represented by the plurality of pixels; a support portion that supports a photosensitive recording medium for recording a recorded image according to the display image in a state in which an exposure surface of the photosensitive recording medium faces the image display device; a louver film that is provided between the image display device and the support portion, and limits an angle of the light radiated from the image display device to the photosensitive recording medium; and a controller that controls the image display device to display the display image in which an image quality of an input image represented by input image data is deteriorated by emphasizing a density difference of a high-frequency component of the input image.

A method and an apparatus are provided for sharpening an image, by an image processor of an electronic device. An input image is received. Low pass filtering is applied to the input image to generate a first image and a second image. A kernel size of first image and the second image are different. Edge preserving filtering is applied to the input image to generate a third image and a fourth image. A kernel size of the third image and the fourth image are different. The first image is subtracted from the third image to obtain a first resulting image. The first image has a larger kernel size than the third image. The second image from the fourth image to obtain a second resulting image. The second image has a larger kernel size than the fourth image. The first resultant image, the second resultant image, and the input image are summed to generate a sharpened image.

A multi-aperture imaging device that is, on the one hand, able to provide image information on a scene and, on the other hand, allows obtaining high lateral resolution and/or a wide total field of view, is described. The multi-aperture imaging device is provided with a first plurality of optical channels for projecting overlapping first partial fields of view of a total field of view on first image sensor areas of an image sensor of the multi-aperture imaging device, as well as with a second arrangement of optical channels for projecting at least a part of of the total field of view on a second image sensor area of the image sensor.

Systems and methods for removing objects from images are disclosed. An image processing application identifies a boundary of each object of a set of objects in an image. In some cases, the identification uses deep learning. The image processing application identifies a completed boundary for each object of the set of objects by providing the object to a trained model. The image processing application determines a set of masks. Each mask corresponds to an object of the set of objects and represents a region of the image defined by an intersection of the boundary of the object and the boundary of a target object to be removed from the image. The image processing application updates each mask by separately performing content filling on the corresponding region. The image processing application creates an output image by merging each of the updated masks with portions of the image.

Disclosed are a method and apparatus for embedding a graphic image representation into a two dimensional matrix code by modifying the characteristic values of individual pixels in the image according the values of a provided two dimensional matrix code image. The modified character pixel values are determined using an optimization procedure that minimizes a visual distortion with respect to the original graphic image representation while maintaining the value of a probability of error model below a specified limit.

A radiographic image processing apparatus includes a hardware processor, which determines the intensity of an edge in a radiographic image obtained by radiographically imaging a subject, sets a weighting factor to be used in extracting a frequency component from the radiographic image according to a determination result of the edge intensity, extracts the frequency component from the radiographic image using the weighting factor having been set, multiplies the extracted frequency component by a scattered radiation content rate to estimate a scattered radiation component in the radiographic image, multiplies the estimated scattered radiation component by a scattered radiation removal rate to generate a scattered radiation image representing the scattered radiation component to be removed from the radiographic image, and performs scattered radiation correction on the radiographic image by subtracting the scattered radiation image from the radiographic image.

A generation unit generates, from a first image, a second image from which a first frequency component of the first image has been removed. A correction unit generates a first correction image by adding, to the first image, a first correction component that is based on the first frequency component of the first image and a second frequency component corresponding to a lower band of the first image than the first frequency component, and generates a second correction image by adding, to the second image, a second correction component that is based on the second frequency component. The first correction component includes a component obtained by applying a first gain to the second frequency component. The second correction component includes a component obtained by applying a second gain larger than the first gain to the second frequency component.

Ophthalmological mages generated by coherent imaging modalities have multiple types of noise, including random noise caused by the imaging system and speckle noise caused by turbid objects such as living tissues. These noises can occur at different levels in different locations. A noise-reduction method and system of the present disclosure thus relates to applying different filters for different types of noise and/or different locations of images, sequentially or in parallel and combined, to produce a final noise-reduced image.

A method for masking sensitive data based on image recognition comprises: extracting initial image features of a to-be-processed image in multiple dimensions of features; reducing dimensions for the initial image features in the multiple dimensions of features, to obtain image features of the to-be-processed image in at least one dimension of sensitive data masking; identifying sensitive features of the to-be-processed image based on the image features in the at least one dimension of sensitive data masking; masking the sensitive data for the sensitive features of the to-be-processed image. The method for masking sensitive data based on image recognition realizes the sensitive data masking for images based on image recognition, and the efficiency of sensitive data masking is relatively high.

An image processing apparatus includes: a calculation unit that calculates a size of a target object on an occasion when the target object exists along a peripheral edge part of a captured image captured by an external image capturing apparatus, based on a plurality of images containing the target object that needs to undergo image processing for protecting privacy; a determination unit that determines a region, on an image, that is captured in a state where a part of the target object protrudes from a peripheral edge part of the captured image, based on the size of the target object calculated by the calculation unit; and an image processing unit that performs the image processing on the region on the image determined by the determination unit.