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2383 results about "Pixel based" patented technology

Pixel art is a raster-based digital work that is created on a pixel-by-pixel level. Typically very small, the art form is similar to mosaics or cross-stitch in that it focuses on small pieces placed individually to create a larger piece of art.

Statistical metering and filtering of content via pixel-based metadata

Data supplied to a display having a plurality of pixels comprises both content to be displayed and metadata that identifies the content of the respective pixel as being of a particular type by setting the metadata for each pixel to a value that is one of a predefined set of values. The identification of the content as being of a particular type enables the classification of the pixels on a per pixel basis into one or more categories. Pixels containing data for an advertisement can be identified and metered to determine the total display space they occupy and length of time they are displayed, which are both considered measures of the effectiveness of the advertisement. This metering can therefore be used to more equitably charge for advertising on web pages because an advertiser can be charged on the basis of what a user actually sees on the display. If only a percentage of the advertisement is visible, the advertiser pays an amount in proportion to the percentage of the advertisement that is visible. Pixels belonging to an advertisement can also be metered by a video game in a manner that gives an incentive to a game player to view advertisements. Additionally, metadata can be used to identify a pixel as containing objectionable content or some other information or type of content not desired by a user. The pixels containing objectionable or undesired content, which usually are pixels that display an object or portions thereof, can then be filtered out of the picture in a more precise way to either delete or leave a blurred image of the object or objectionable/undesirable portion thereof only, without hiding an entire screen of data.
Owner:NOKIA TECHNOLOGLES OY

Converting low-dose to higher dose 3D tomosynthesis images through machine-learning processes

A method and system for converting low-dose tomosynthesis projection images or reconstructed slices images with noise into higher quality, less noise, higher-dose-like tomosynthesis reconstructed slices, using of a trainable nonlinear regression (TNR) model with a patch-input-pixel-output scheme called a pixel-based TNR (PTNR). An image patch is extracted from an input raw projection views (images) of a breast acquired at a reduced x-ray radiation dose (lower-dose), and pixel values in the patch are entered into the PTNR as input. The output of the PTNR is a single pixel that corresponds to a center pixel of the input image patch. The PTNR is trained with matched pairs of raw projection views (images together with corresponding desired x-ray radiation dose raw projection views (images) (higher-dose). Through the training, the PTNR learns to convert low-dose raw projection images to high-dose-like raw projection images. Once trained, the trained PTNR does not require the higher-dose raw projection images anymore. When a new reduced x-ray radiation dose (low dose) raw projection images is entered, the trained PTNR outputs a pixel value similar to its desired pixel value, in other words, it outputs high-dose-like raw projection images where noise and artifacts due to low radiation dose are substantially reduced, i.e., a higher image quality. Then, from the “high-dose-like” projection views (images), “high-dose-like” 3D tomosynthesis slices are reconstructed by using a tomosynthesis reconstruction algorithm. With the “virtual high-dose” tomosynthesis reconstruction slices, the detectability of lesions and clinically important findings such as masses and microcalcifications can be improved.
Owner:ALARA SYST

Deep learning-based traffic sign automatic identifying and marking method

The invention provides a deep learning-based traffic sign automatic identifying and marking method, which is used in the technical field of environmental perception of intelligent vehicles. A semantic segmentation structure is adopted for locating and detecting traffic signs, and candidate regions with the traffic signs are obtained, wherein the semantic segmentation structure comprises two parts: an encoding network; and a decoding network and a pixel-based classification layer. Then, the traffic signs in the candidate regions are subjected to classified identification and locating through a convolutional neural network of a quick region. Based on the traffic sign automatic identifying and marking method, the invention furthermore correspondingly provides an effective map navigation information updating method. According to the method, the candidate regions with the traffic signs are located by using the semantic segmentation method, so that a new idea is provided, a training parameter quantity is reduced, the storage space is saved, and the computing time is shortened; and the method is high in identifying accuracy, and can perform relatively accurate traffic sign information updating on map navigation information, thereby better serving drivers conveniently.
Owner:BEIHANG UNIV

Method and apparatus for motion blur and ghosting prevention in imaging system

A method and apparatus for motion blur and ghosting prevention in imaging system is presented. A residue image is computed by performing spatial-temporal filter with a set of absolute image difference of image pairs from input images. A noise adaptive pixel threshold is computed for every pixel based on noise statistics of image sensor. The residue image and the noise adaptive pixel threshold are used to create a motion masking map. The motion masking map is used to represent motion and non-motion pixels in pixels merging. The pixels merging step is performed to generate an output image by considering the motion pixels where the motion pixels are performed separately. The resulting output image having no or less motion blur and ghosting artifacts can be obtained, even the input images having different degree of motion blur between each of the image, while the complexity is low. It is preferred that the current invention is applied in the Bayer raw domain. The benefit is reduced computation and memory because only 1 color component is processed for each pixel. Another benefit is higher signal fidelity because processing in the Bayer raw domain is unaffected by demosaicing artifacts, especially along edges. However, the current invention can also be applied in RGB domain.
Owner:PANASONIC CORP
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