Adaptive imaging methods and systems for generating enhanced low light video of an object for medical visualization are disclosed and include acquiring, with an image acquisition assembly, a sequence of reference frames and/or a sequence of low light video frames depicting the object, assessing relative movement between the image acquisition assembly and the object based on at least a portion of the acquired sequence of reference video frames or the acquired sequence of low light video frames, adjusting a level of image processing of the low light video frames based at least in part on the relative movement between the image acquisition assembly and the object, and generating a characteristic low light video output from a quantity of the low light video frames, wherein the quantity of the low light video frames is based on the adjusted level of image processing of the low light video frames.

[Object] To provide stable infrared images. [Solution] Provided is an image processing device including: an acquisition unit that acquires an infrared image; and a control unit that variably controls a target wavelength of the infrared image acquired by the acquisition unit and controls gradation of the infrared image depending on the target wavelength.

An information processing apparatus includes a processor configured to infer an object represented in image data to be processed, the object being inferred by using a learning model for inferring the object represented in the image data, and perform image processing on the image data with a correction level of the image processing for correcting the image data being varied on a basis of a probability of correctness in inference of the object.

There is provided with an image shake correction device that controls an image correction unit and corrects an image shake of a captured image. The image shake correction device calculates a first correction amount to be used for correcting the image shake while shooting moving images and a second correction amount to be used for correcting the image shake while shooting still images based on a shake detection signal. The image shake correction device selects the correction amount to be used for correcting the image shake from either the first correction amount or the second correction amount and executes a control that updates an intermediate calculation value of the calculation unit corresponding to the correction amount that has not been selected from either the first calculation unit or the second calculation unit, with a value of the correction amount that has been selected.

A method, a computer and a non-transitory computer readable medium for deblurring, the method may include receiving an input image; calculating, based on the input image, a first estimated blur kernel; calculating a first estimate of a latent image based on the input image and the first estimated blur kernel; and performing at least one repetitions of: receiving a current estimate of the latent image; calculating, based on the current estimate of the latent image, a next estimated blur kernel; and calculating a next estimate of the latent image based on the current estimate of the latent image and the next estimated blur kernel

The present invention provides an image restoration apparatus, a camera and a program which are capable of performing image restoration with simple const ruction. A specific area within a captured image is specified, and a calculation of a point spread function and the image restoration calculation are carried out using an image in the specific area.

According to one embodiment, an ultrasonic diagnostic apparatus includes an image acquisition unit configured to acquire an ultrasonic image, a first calculation unit which calculates directions of edges in a local region in the ultrasonic image, sizes of the edges in the local region, and directional uniformity of the edges in the local region, a second calculation unit which calculates a composite coefficient by using the sizes of the edges and the directional uniformity of the edges, a third calculation unit which calculates a filtering coefficient for a region corresponding to the local region based on the composite coefficient, and a filtering unit which performs filtering processing for sharpening or smoothing the ultrasonic image with respect to the ultrasonic image by using the filtering coefficient.

Techniques are provided for improving image data quality, such as in functional imaging follow-up studies, using reconstruction, post-processing, and/or deep-learning enhancement approaches in a way that automatically improves analysis fidelity, such as lesion tracking fidelity. The disclosed approaches may be useful in improving the performance of automatic analysis methods as well as in facilitating reviews performed by clinician.

An electronic device configured to control a host vehicle includes: an image sensor configured to photograph a surrounding environment of the host vehicle; and a processor configured to perform an image processing operation based on a first image captured by the image sensor, and control the host vehicle based on the processing result, wherein the processor determines whether to use a high speed performance of the image processing operation based on a speed of the host vehicle, and the electronic device is configured such that when the high speed performance is not used, the processor performs the image processing operation by using a first image processing module, and when the high speed performance is used, the processor performs the image processing operation by using a second image processing module having less data throughput than the first image processing module.

According to one embodiment, an ultrasonic diagnostic apparatus according to one embodiment transmits an ultrasonic wave into a predetermined region including a diagnosis target of an object, receives a reflected wave from the predetermined region, and acquires ultrasonic image data based on the reflected wave and comprises a correction unit which executes tone correction of the ultrasonic image data, and in the tone correction, the correction unit calculates a histogram associated with brightness of the image data and calculates a brightness distribution range corresponding to the diagnosis target and a tone correction function using the histogram.