An image stabilization control apparatus comprising: a first receiving unit that receives a translational shake signal that indicates a translational shake in a first direction; a second receiving unit that receives a first rotational shake signal that indicates a rotational shake about a first axis that intersects with the direction of gravity and the first direction; a first calculation unit that finds a first fluctuation range of a gravitational component in the first direction based on the first rotational shake signal; a second calculation unit that finds an amount of shake in the first direction based on the translational shake signal and the first fluctuation range; and a third calculation unit that finds a target value for reducing a shake in the first direction based on the amount of shake found by the second calculation unit.

An electronic device is provided. The electronic device includes at least one processor, and a memory functionally connected to the at least one processor. The memory may store instructions that, when executed, enable the electronic device to obtain a plurality of images, generate a first basic extended image based on first images among the plurality of images, identify at least one first masking area included in the first basic extended image, and generate a first inference image by modifying the at least one first masking area using at least one first inference result, based on the first images and the first basic extended image. An angle of view of the first inference image may be larger than an angle of view of each of the first images.

An image processing device of an embodiment includes a control unit that generates a composite image and outputs the composite image to a display device, the composite image being acquired by combination of a first image captured in first exposure time and having first resolution, and a second image that is an image corresponding to a part of a region of the first image, and that is captured in second exposure time shorter than the first exposure time and has second resolution higher than the first resolution, the first image and the second image being input from an image sensor.

Provided are a signal processing device, a signal processing method, a signal processing program, an imaging apparatus, and a lens apparatus capable of accurately calculating an amount of blurring on the basis of a signal which is output from a blurring detection sensor. The signal processing device processes a signal which is output from a blurring detection sensor in progress of exposure of an imaging element. The signal processing device includes a processor. The processor is configured to perform processing of generating a second signal obtained by performing high-pass filter processing on a first signal which is output from the blurring detection sensor; and processing of calculating an amount of blurring on the basis of the first signal or the second signal.

Depth information can be used to assist with image processing functionality, such as image stabilization and blur reduction. In at least some embodiments, depth information obtained from stereo imaging or distance sensing, for example, can be used to determine a foreground object and background object(s) for an image or frame of video. The foreground object then can be located in later frames of video or subsequent images. Small offsets of the foreground object can be determined, and the offset accounted for by adjusting the subsequent frames or images. Such an approach provides image stabilization for at least a foreground object, while providing simplified processing and reduce power consumption. Similarly processes can be used to reduce blur for an identified foreground object in a series of images, where the blur of the identified object is analyzed.

A digital graduated filter is implemented in an imaging device by combining multiple images of the subject wherein the combining may include combining different numbers of images for highlights and for shadows of the subject. The imaging device may present a user with a set of pre-defined graduated filter configurations to choose from. A user may also specify the direction of graduation and strength of graduation in a viewfinder. In an alternative implementation, combining may include scaling of pixels being added instead of varying the number of images being combined. In an alternative implementation, the combining of multiple images may include combining a different number of images for highlights of the subject than for shadows of subject.

In an image adjustment system, an image display device displays a captured image that is adjusted by an image adjustment device. The image adjustment device includes an image processor and an image generator. The image generator generates a spherical surface image. The image processor acquires the spherical surface image from the image generator to display the spherical surface image on the image display device on the basis of instruction information output from a controller. The image generator adjusts the captured image in accordance with a rotation of the spherical surface image, corrects camera shake in the captured image adjusted, and determines that a travel direction of a camera is changed when the captured image that is camera-shake corrected is changed by a predetermined angle or greater.

An image capture device may capture a video while experiencing motion. Motion of the image capture device during video capture may be determined based on optical flow and structure from motion solve of the video. Optical flow derived motion and/or the motion solve derived motion of the image capture device may be selected to perform stabilization of the video.

Positions of an image capture device during capture of a video may be transferred to a computing device before the video is transferred to the computing device. The positions of the image capture device may be used to determine a viewing window for the video before the video is obtained. The viewing window may be used to present a stabilized view of the video when the video is obtained. For example, a stabilized view of the video may be presented as the video is streamed to the computing device.

A method for detecting a complexity of a traveling scenario of a vehicle includes obtaining a travelling speed of the vehicle and a travelling speed of a target vehicle, determining, based on the traveling speed of the vehicle and the traveling speed of the target vehicle, a dynamic complexity of a traveling scenario in which the vehicle is located, determining static information of each static factor in the traveling scenario in which the vehicle is currently located, obtaining, based on the static information of each static factor, a static complexity of the traveling scenario in which the vehicle is located, and obtaining, based on the dynamic complexity and the static complexity, a comprehensive complexity of the traveling scenario in which the vehicle is located.