Stereoscopic display technologies are provided. A computing device generates a stereoscopic display of an object by coordinating a first image and a second image. To reduce discomfort or to reduce diplopic content, the computing device may adjust at least one display property of the first image and/or the second image depending on one or more factors. The factors may include a time period associated with the display of the object, the vergence distance to the object, the distance to the focal plane of the display, contextual data interpreted from the images and/or any combination of these and other factors. Adjustments to the display properties can include a modification of one or more contrast properties and/or other modifications to the images. The adjustment to the display properties may be applied with varying levels of intensity and/or be applied at different times depending on one or more factors and/or contextual information.

A device system and methods comprising receiving a stereoscopic video or image of a scene including two perspective data streams (e.g. left and right) captured for example by a stereoscopic sensing device and analyzing the two perspective data streams based on predefined stereoscopic discomfort data and the depth map to yield one or more stereoscopic parameters; measure/process said stereoscopic parameters; assigning/calculating weight for one or more stereoscopic effects of said two perspective data streams of a scene according to the measured stereoscopic parameters; sum the weighted one or more stereoscopic effects to generate information of the impact of said one or more stereoscopic effects on a viewer of said 3D content.

Systems and methods may provide for utilizing stereoscopic inputs to take advantage of a codec to improve encoding and processing efficiency. The left and right channels of the stereoscopic inputs provide inputs for views of the same image frames. The frames may be offset by the parallax effect. The systems and methods utilize similarities between the left and right channels to allow motions (i.e., motion vectors) related to an object in the scene for one view to be spatially translated for the other view based on known differences in distance and geometry to avoid the necessity to encode and process both channel views. The system and method thereby improves the encoding and processing efficiency of motion processes such as motion vectors, motion sampling, macroblock sampling, edge sampling and the like.

An image processing apparatus (204) includes an unnecessary component determiner (204a) which determines unnecessary component information of a parallax image based on difference information relating to a plurality of parallax images, a reduction processor (204b) which performs reduction processing on at least one of the parallax image, the difference information, and the unnecessary component information, a magnification processor (204c) which performs magnification processing on the unnecessary component information, and an unnecessary component reducer (204d) which reduces an unnecessary component, based on the unnecessary component information, from the parallax image or a synthesized image obtained by synthesizing the plurality of parallax images.

Provided is a system and method that can simultaneously check if a camera is subjected to lack of focus (e.g., blur), movement, obstruction, improper zoom, improper pan, or the like, using a single reference image. The system does not require deep learning or training thus keeping the system lightweight. In one example, the method may include receiving an image of a scene captured by a camera, applying a filter to the image corresponding to an image attribute of the camera to generate filtered image and applying the filter to a reference image of the scene to generate a filtered reference image, respectively, determining that a quality of the image attribute of the camera has degraded based on a comparison of the filtered image to the filtered reference image, and displaying an alert on a user interface with information about the degradation of the quality of the image attribute.

An image processing apparatus includes an acquisition unit configured to acquire position information indicating a position of a light source for irradiating an object with light, an acquisition unit configured to acquire position information indicating a position where a normal is acquired in the object, an acquisition unit configured to acquire position information indicating a position of an image capturing apparatus for imaging the object irradiated with the light by the light source, a calculation unit configured to, based on the position information, calculate a normal at the position where a normal is acquired, and a correction unit configured to, according to a predetermined condition, correct the position where a normal is acquired, wherein in a case where the correction unit corrects the position where a normal is acquired, the calculation unit calculates a normal at the corrected position where a normal is acquired.

Mobile phones and other portable devices are equipped with a variety of technologies by which existing functionality can be improved, and new functionality can be provided. Some aspects relate to visual search capabilities, and determining appropriate actions responsive to different image inputs. Others relate to processing of image data. Still others concern metadata generation, processing, and representation. Yet others concern user interface improvements. Other aspects relate to imaging architectures, in which a mobile phone's image sensor is one in a chain of stages that successively act on packetized instructions/data, to capture and later process imagery. Still other aspects relate to distribution of processing tasks between the mobile device and remote resources (the cloud). Elemental image processing (e.g., simple filtering and edge detection) can be performed on the mobile phone, while other operations can be referred out to remote service providers. The remote service providers can be selected using techniques such as reverse auctions, through which they compete for processing tasks. A great number of other features and arrangements are also detailed.

This application provides an image processing method and an electronic device. The method includes: obtaining a first image and a second image that are acquired at a same acquisition moment, where the first image is obtained by using a first photographing unit to acquire an image in a first acquisition region, and the second image is obtained by using a second photographing unit to acquire an image in a second acquisition region, where a parameter of the first photographing unit and a parameter of the second photographing unit are the same, and there is an overlapping acquisition region between the first acquisition region and the second acquisition region; and determining, according to the first image and the second image, whether the first photographing unit and the second photographing unit are normal.

In an image processing apparatus, an image acquiring unit acquires a first image and a second image that form stereoscopic images. A first sub-image extracting unit extracts first sub-images from the first image. A second sub-image extracting unit extracts second sub-images from the second image. A matching unit matches each pair of the first and second sub-images to determine a degree of similarity therebetween. A similar sub-image setting unit sets the second sub-image having a highest degree of similarity to the first sub-image to be a similar sub-image to the first sub-image. A brightness comparing unit compares in brightness each pair of the first and second sub-images. The matching unit is configured to, if a result of comparison made by the brightness comparing unit between a pair of the first and second sub-images is out of a predetermined brightness range, exclude such a pair of the first and second sub-images.

A simulated method and system for surgical instrument based on tomography are provided, in which the method includes obtaining a biological stereoscopic image and inputting a parameter set of an implant to be implanted; denoting a target position and an initial position in the biological stereoscopic image; estimating a dimensional coordinate of a contact area of the implant and a living organism when the implant has been implanted into the living organism based on the parameter set, the target position and the initial position in the biological stereoscopic image; and obtaining a physiological data set by re-sampling corresponding to the dimensional coordinate of the implant in the living organism for evaluating the effect after the implant has been implanted into the living organism. The surgeons may evaluate the effect after implantation of implant into the living organism by using the aforementioned simulated method, thereby enhancing the overall quality and result of the surgery.