Abstract: The present invention provides methods of preparing aggregated pluripotent stem cell clusters for differentiation.

Abstract: The present invention provides methods of preparing aggregated pluripotent stem cell clusters for differentiation. Specifically, the invention discloses methods of differentiating pluripotent cells into beta cell, cardiac cell and neuronal cell lineages using suspension clustering. The methods involve preparing the aggregated cell clusters followed by differentiation of these clusters.

Abstract: Techniques are provided herein for utilizing an inventory engine to optimize the selection of a set of items to be stored as inventory at a storage location. A candidate set of items may be identified based at least in part on a selection model. In accordance with at least one embodiment, the selection model may be based at least in part on a capacity of the storage location and a threshold time duration by which purchased items of the set of items are to be transported from the storage location to a purchaser. A plurality of probability values corresponding to the candidate set of items may be determined. An optimal set of items may be determined based at least in part on the candidate set of items and the plurality of probability values.

Abstract: The present invention provides methods of preparing aggregated pluripotent stem cell clusters for differentiation. Specifically, the invention discloses methods of differentiating pluripotent cells into beta cell, cardiac cell and neuronal cell lineages using suspension clustering. The methods involve preparing the aggregated cell clusters followed by differentiation of these clusters.

Abstract: The present invention provides methods of preparing aggregated pluripotent stem cell clusters for differentiation.

Abstract: Systems and methods are disclosed for determining the perceptibility of noise in a block of images and/or video. The systems and methods may compute a mask value for the block using a block masking generator. The mask value may indicate the perceptibility of noise in the block. The mask value may be computed using a normalized activity value and/or a texture value for the block. The normalized activity value may indicate the relative activity in the block as compared to the activity in the image and/or video. The texture value may indicate the strength and/or number of edges in the block.

Abstract: The appearance of image details can be preserved and/or enhanced by applying contrast adaptive gain to the high spatial frequency component of the luminance information. The image details in bright and/or dark regions can be further boosted by applying a local mean adaptive gain. The contrast transfer mapping curve for luminance contrast enhancement can be re-scaled to account for the applied gain. The re-scaling may be performed from frame to frame of displayed video. The re-scaling may be temporally controlled for subsequent frames to make the re-scaling change gradually to prevent flickering.

Abstract: A method and apparatus are disclosed for identifying and removing banding artifacts (i.e., false contours) resulting from insufficient bit depth caused by digital image quantization, conversion, and/or compression. This method includes: explicitly identifying texture block and flat block; de-termination of filter window sizes with the consideration of handling transitions between texture block and flat block; de-banding filtering with edge protection; and noise shaping according to de-banding filter result.

Abstract: Provided are a digital video rescaling system, a method of rescaling video images, and a chip comprising a computer executable medium embedded therein computer executable instructions for rescaling video images.

Abstract: A method and apparatus are disclosed for identifying and removing banding artifacts (i.e., false contours) resulting from insufficient bit depth caused by digital image quantization, conversion, and/or compression. This method includes: explicitly identifying texture block and flat block; de-termination of filter window sizes with the consideration of handling transitions between texture block and flat block; de-banding filtering with edge protection; and noise shaping according to de-banding filter result.

Abstract: Systems and methods are disclosed for determining the perceptibility of noise in a block of images and/or video. The systems and methods may compute a mask value for the block using a block masking generator. The mask value may indicate the perceptibility of noise in the block. The mask value may be computed using a normalized activity value and/or a texture value for the block. The normalized activity value may indicate the relative activity in the block as compared to the activity in the image and/or video. The texture value may indicate the strength and/or number of edges in the block.

Abstract: A frame level noise estimate for an image can be determined. An image processor includes a high pass filter unit configured to perform high-pass spatial filtering of image data for first and second frames to produce high-pass spatially filtered information for the first frame and the second frame. A cumulative histogram generator is configured to analyze the high-pass spatially filtered information for the first frame and the second frame to produce a first cumulative histogram for the first frame and a second cumulative histogram for the second frame. A comparator is configured to determine a difference value between the first and second cumulative histograms. A mapping unit is configured to determine an estimated noise value based on the difference value.

Abstract: A video image processing system is described that generates the interpolated video images with sharp and jaggedness-free edges. A method of video image processing is also described that interpolates video images to generate the video images with sharp and jaggedness-free edges. The video image processing system receives and makes input image data available for further processing; analyzes the local features of the input image data; filters the input image data before performing interpolation process; modifies the phase value adaptive to the local edge distance; rescales the input image data in horizontal interpolation using the modified phase value; and rescales the horizontally interpolated image data in vertical interpolation using modified phase value.

Abstract: The appearance of image details can be preserved and/or enhanced by applying contrast adaptive gain to the high spatial frequency component of the luminance information. The image details in bright and/or dark regions can be further boosted by applying a local mean adaptive gain. The contrast transfer mapping curve for luminance contrast enhancement can be re-scaled to account for the applied gain. The re-scaling may be performed from frame to frame of displayed video. The re-scaling may be temporally controlled for subsequent frames to make the re-scaling change gradually to prevent flickering.

Abstract: A device processes an initial digital image with at least one contour zone. The device may have a magnifier able to magnify the initial image into a magnified digital image. The magnifier may have a detector able to detect the contour zones of the initial digital image, a determinater able to determine the size, in terms of number of pixels, of each contour zone, and a second magnifier able to magnify each contour zone using of a software tool, chosen as a function of the size of each contour zone, from among a set of magnifying software tools.

Abstract: Provided are a digital video rescaling system, a method of rescaling video images, and a chip comprising a computer executable medium embedded therein computer executable instructions for rescaling video images.

Abstract: A video image processing system is described that generates the interpolated video images with sharp and jaggedness-free edges. A method of video image processing is also described that interpolates video images to generate the video images with sharp and jaggedness-free edges. The video image processing system receives and makes input image data available for further processing; analyzes the local features of the input image data; filters the input image data before performing interpolation process; modifies the phase value adaptive to the local edge distance; rescales the input image data in horizontal interpolation using the modified phase value; and rescales the horizontally interpolated image data in vertical interpolation using modified phase value.

Abstract: A device processes an initial digital image with at least one contour zone. The device may have a magnifier able to magnify the initial image into a magnified digital image. The magnifier may have a detector able to detect the contour zones of the initial digital image, a determinater able to determine the size, in terms of number of pixels, of each contour zone, and a second magnifier able to magnify each contour zone using of a software tool, chosen as a function of the size of each contour zone, from among a set of magnifying software tools.