Abstract: Systems and methods for processing YCC image data provided. In one example, an electronic device includes memory to store image data in RGB or YCC format and a YCC image processing pipeline to process the image data. The YCC image processing pipeline may include receiving logic configured to receive the image data in RGB or YCC format and color space conversion logic configured to, when the image data is received in RGB format, convert the image data into YCC format. The YCC image processing logic may also include luma sharpening and chroma suppression logic; brightness, contrast, and color adjustment logic; gamma logic; chroma decimation logic; scaling logic; and chroma noise reduction logic.

Abstract: Methods and Systems for aligning multiple video sequences of a similar scene. It is determined which video sequences should be aligned with each other using linear dynamic system (LDS) modeling. The video sequences are then spatially aligned with each other.

Abstract: A color translation method and a color translation apparatus adapted to map a data point from a first color space to a second color space are provided. At least four color axes coordinating with a plurality of first reference points and a plurality of second reference points corresponding to the first reference points are used to divide the first color space and second color space into a plurality of first sub-spaces and a plurality of second sub-spaces. A target first sub-space where the data point is located is found, and then a corresponding target second sub-space is also found. According to a positional relationship between the data point and the first reference points which define the target first sub-space, an interpolation operation is applied to the second reference points which define the target second sub-space so as to obtain a mapped point in the second color space.

Abstract: A method for removing boundary distortion includes receiving a one-dimensional input signal and determining whether the one-dimensional input signal includes an even number of data elements. If the one-dimensional input signal includes an even number of data elements, an extrapolation operation is performed on one of a first or second boundary of the one-dimensional input signal. The extrapolation operation produces one additional data element. The method may further include performing a mirroring operation on the signal data resulting from the extrapolation operation to produce a mirrored signal, and performing a transform operation the mirrored signal.

Abstract: Disclosed is a parallel intra prediction method for video data, including: dividing, by an intra prediction unit, pixels included in at least one prediction unit configuring a coding unit or a sub-coding unit so as to belong to any one of a reference pixel group and a prediction group; generating, by the intra prediction unit, reference sub blocks and prediction sub blocks, respectively, using reference pixels belonging to the reference pixel group and prediction pixels belonging to the prediction pixel group; performing, by the intra prediction unit, encoding processing on the reference sub blocks; and performing, by the intra prediction unit, encoding processing on the prediction sub blocks.

Abstract: A dependency indication is signaled within the beginning of a packet, that is, within the adjacent of a slice header to be parsed or a parameter set. This is achieved, for example, by including the dependency indication at the beginning of the slice header, preferably after a syntax element identifying the parameter set and before the slice address, by including the dependency indication before the slice address, by providing the dependency indication to a NALU header using a separate message, or by using a special NALU type for NALUs carrying dependent slices.

Abstract: A method for comparing a first image with a second image. The method identifies first keypoints in the first image and second keypoints in the second image and associates each first keypoint with a corresponding second keypoint to form a corresponding keypoint match. For each pair of first keypoints, the method further calculates the distance therebetween for obtaining a corresponding first length. Similarly, for each pair of second keypoints, the method calculates the distance therebetween for obtaining a corresponding second length. The method further calculates a plurality of distance ratios; each distance ratio is based on a length ratio between a selected one between a first length and a second length and a corresponding selected one between a second length and a first length, respectively.

Abstract: An image processing apparatus separates a captured image into a region of object (B) 1001B and a region of object (A) 1001A shallower than the region of object (B) 1001B in depth indicated by depth information, duplicates pixels constituting the region of object (B) 1001B and positioned in neighborhood of boundary between the region of object (B) 1001B and the region of object (A) 1001A, onto the neighborhood of the boundary outside the region of object (B) 1001B, thereby generating an extended region (B) 5001B, performs blur processing on the extended region (B) 5001B and the region of object (A) 1001A based on the depth of the region of object (A) 1001A indicated by the depth information, and after the processing, composites a value of each pixel constituting the extended region (B) 5001B and a value of one of pixels constituting the region of object (A) 1001A corresponding in position.

Abstract: A temporal noise reduction method and a temporal noise reduction device are provided. The temporal noise reduction device includes a temporal filter unit that performs a temporal filtering operation using pixel values (CP) of an N×M array in a current frame and pixel values (FP) of an N×M array located at the same position in a neighboring frame separated by a distance TP from the current frame and a motion filter unit that detects a motion of a pixel image from the resultant values of the temporal filter unit and that eliminates noise of a motion-abundant pixel value using a spatial filter. It is possible to effectively reduce noise of an image to prevent deterioration in image quality of the image and to improve performance of post-processing techniques.

Abstract: The invention relates to methods and apparatuses for encoding/decoding high resolution images, which involve setting the size of the prediction unit to be encoded to an expanded macro-block size in accordance with the temporal frequency characteristics or spatial frequency characteristics among pictures to be encoded, and performing motion prediction motion compensation, and transformation on the basis of a set prediction unit size. In addition, the methods and the apparatuses of the present invention involve dividing a macro-block having a pixel size of 32*32 or 64*64 into at least one partition on the basis of an edge, and performing encoding processes for each partition. Accordingly, encoding efficiency can be improved for high definition (HD) or higher resolution high-resolution images.

Abstract: An image processing apparatus includes an exaggeration unit configured to perform on an original image including a hand-drawn element an exaggeration process that expands the hand-drawn element to generate an exaggerated image; and a reduction unit configured to reduce the exaggerated image to generate a reduced image of a predetermined size smaller than a size of the original image.

Abstract: Techniques are provided for determining depth to objects. A depth image may be determined based on two light intensity images. This technique may compensate for differences in reflectivity of objects in the field of view. However, there may be some misalignment between pixels in the two light intensity images. An iterative process may be used to relax a requirement for an exact match between the light intensity images. The iterative process may involve modifying one of the light intensity images based on a smoothed version of a depth image that is generated from the two light intensity images. Then, new values may be determined for the depth image based on the modified image and the other light intensity image. Thus, pixel misalignment between the two light intensity images may be compensated.

Abstract: A system and a method for identification of alphanumeric characters present in a series in an image are disclosed. The system and method captures the image and further processes it for binarization by computing a pattern of the image. The generated binarized images are then filtered for removing unwanted components. Candidate images are identified out of the filtered binarized images. All the obtained candidate images are combined to generate a final candidate image which is further segmented in order to recognize a valid alphanumeric character present in the series.

Abstract: Disclosed is an image processing apparatus for converting an original image. Processing of blurring an input original image is performed to generate a blurred image. A difference image that is the difference between the original image and an adjusted image obtained by adjusting the density of the blurred image is generated. The difference image and the original image are composited based on the density of the difference image and the density of the original image. This allows to easily obtain a painting-like effect even in, for example, a low-contrast portion of an image.

Abstract: An image processing apparatus including a dispersion calculation portion, an ? deriving portion, and a filtering portion, and eliminates mosquito noise from a digitally compressed image having a plurality of color components. The dispersion calculation portion is configured to calculate, for each of the color components of each pixel contained in the digitally compressed image, a dispersion of pixel values of a plurality of pixels contained in a first region in which that pixel serves as a representative pixel. The ? deriving portion is configured to derive, for each pixel contained in the digitally compressed image, a greatest value of the plurality of dispersions that respectively correspond to the plurality of color components of that pixel, or a corrected value of the greatest value, as an ? value of an ? filter for that pixel. The filtering portion is configured to apply the ? filter to the digitally compressed image.

Abstract: The present disclosure generally relates to systems and methods for image data processing. In certain embodiments, an image processing pipeline may compute noise statistics associated with image data by receiving a frame of the image data having a plurality of pixels. The image processing pipeline may then identify a plurality of portions of the frame of the image data such that each portion of the plurality of portions has a flat surface. The image processing pipeline may then calculate a plurality of gradients for each portion of the plurality of portions, determine one or more dominant gradient orientations for each portion of the plurality of portions, and generate a histogram that represents a plurality of dominant gradient orientations that corresponds to the plurality of portions. After generating the histogram, the image processing pipeline may store the histogram, which may represent the noise statistics, in a memory.

Abstract: An apparatus and method are disclosed for improving imaging based on a time-series of images. In one embodiment, a time-series of images are acquired using a same imaging protocol of the same subject area, but the images are spaced in time by one or more time intervals (e.g, 1, 2, 3 . . . seconds apart). A sub-region is projected across all of the images to perform a localized analysis (corresponding X-Y pixels or X-Y-Z voxels are analyzed across all images) that identifies temporal components within each sub-region. In some of the sub-regions, the temporal components are removed when the amplitude of the component is below a predetermined amplitude threshold. The images are then combined using the sub-regions with reduced components in order to obtain a single image with reduced noise.

Abstract: Provided is an image processing apparatus including a hand shape recognition unit that performs hand shape recognition on an input image to detect a position and a size of a hand with a specific shape in the input image, a determination region setting unit that sets a region in a vicinity of the hand on the input image as a determination region used to recognize a gesture performed using the hand, based on the position and the size of the hand, and a gesture recognition unit that recognizes the gesture by monitoring movement of the hand to the determination region.

Abstract: A method for correcting a positron emission tomography (PET) image includes obtaining a magnetic resonance (MR) image dataset, classifying at least one object in the MR image as a bone, generating MR-derived PET attenuation correction factors based on the object classified as the bone, and attenuation correcting a plurality of positron emission tomography (PET) emission data using the MR-derived PET attenuation correction factors. A medical imaging system and a non-transitory computer readable medium are also described herein.

Abstract: Methods, systems, and computer-readable media are provided for computer aided detection. An example method includes determining a pixel threshold value for an analysis of an image selected by a user. The image includes a plurality of pixels. The example method includes determining a segmentation setting for the analysis. The segmentation setting specifies a size of a portion of the image to be used during the analysis. The example method includes analyzing the image by performing a comparison between a first and second segment of the image based on the pixel threshold value and the segmentation setting. The example method includes identifying potential abnormalities in the image based on the analysis.