Abstract: A system and method for effectively performing wavelet transforms on incomplete image data includes an image processor that performs a green-pixel transformation procedure on incomplete color pixel matrices. The image processor then rearranges red, blue and transformed green-pixel into four quadrants of contiguous pixels and applies some two dimensional (2D) wavelet thresholding schemes on each quadrant. After thresholding, an inverse procedure is applied to reconstruct the pixel values on the incomplete color pixel matrices. For further de-correlation of image data, the image processor may stack similar image patches in a three dimensional (3D) array and apply incomplete-data wavelet thresholding on the 3D array. The incomplete-data wavelet thresholding procedure may be put in an improved local similarity measurement framework to achieve better performance of image processing tasks. A CPU device typically controls the image processor to effectively perform the image processing procedure.

Abstract: An image denoising system and method of implementing the image denoising system is described herein. Noise is decomposed within each channel into frequency bands, and sub-band noise is propagated. Denoising is then able to occur at any node in a camera pipeline after accurately predicting noise that is signal level-dependent, frequency dependent and has inter-channel correlation. A methodology is included for estimating image noise in each color channel at a sensor output based on average image level and camera noise parameters. A scheme is implemented for detecting a peak-white image level for each color channel and predicting image level values for representative colors. Based on a noise model and camera parameters, noise levels are predicted for each color channel for each color patch and these noise levels are propagated to the denoising node. A three dimentional LUT correlates signal level to noise level. Then, a denoising threshold is adaptively controlled.

Abstract: A video enhancement processing system improves perceptual quality of video data with limited processing complexity. The system may perform spatial denoising using filter weights that may vary based on estimated noise of an input image. Specifically, estimated noise of the input image may alter a search neighborhood over which the denoising filter operates, may alter a profile of weights to be applied based on pixel distances and may alter a profile of weights to be applied based on similarity of pixels for denoising processes. As such, the system finds application in consumer devices that perform such enhancement techniques in real time using general purpose processors such as CPUs or GPUs.

Abstract: A fast image-based barcode detection and recognition technique allows a user of a device to analyze an image containing a barcode, locating the barcode containing region of the image automatically, without requiring a user to frame and align the image. In one embodiment, the technique may locate multiple omni-directional barcode regions simultaneously.

Abstract: A video enhancement processing system improves perceptual quality of video data with limited processing complexity. The system may perform spatial denoising using filter weights that may vary based on estimated noise of an input image. Specifically, estimated noise of the input image may alter a search neighborhood over which the denoising filter operates, may alter a profile of weights to be applied based on pixel distances and may alter a profile of weights to be applied based on similarity of pixels for denoising processes. As such, the system finds application in consumer devices that perform such enhancement techniques in real time using general purpose processors such as CPUs or GPUs.

Abstract: Image enhancement by separating the image signals, either Y or RGB, into a series of bands and performing noise reduction on bands below a given frequency but not on bands above that frequency. The bands are summed to develop the image enhanced signals. This results in improved sharpness and masking of image processing pipeline artifacts. Chroma signals are not separated into bands but have noise reduction applied to the full bandwidth signals. The higher frequency band is attenuated or amplified based on light level. The noise reduction has thresholds based on measured parameters, such as signal frequency, gain and light level, provided in a lookup table. The window size used for the noise reduction varies with the light level as well, smaller windows sizes being used in bright light and increasing window sizes as light levels decrease. Panoramic images are handled in a similar fashion.

Abstract: A fast image-based barcode detection and recognition technique allows a user of a device to analyze an image containing a barcode, locating the barcode containing region of the image automatically, without requiring a user to frame and align the image. In one embodiment, the technique may locate multiple omni-directional barcode regions simultaneously.

Abstract: A method and apparatus of in-painting an image using prioritized graph cut optimization is disclosed. In one embodiment, the method includes examining an image comprising a plurality of pixels that form a source region and a target region, wherein the source region comprises pixel information partitioning the source region into blocks, defining boundary areas comprising a portion of the source region and a portion of the target region, computing a plurality of energy values for the source region and the boundary areas, wherein energy values represent intensity comparisons between the boundary areas and neighboring blocks of the source region and assigning labels to the boundary areas using on a graph-cut technique, wherein each label is associated with a neighboring block and an minimal energy value for each boundary area and storing pixel information based on the pixel information of the neighboring blocks associated with the minimal energy values.

Abstract: Systems, methods, and computer readable media for removing noise from the luminance (luma) channel in a digital image represented in the YUV color space are described. In general, an element from the luma channel may be selected and a region about that element defined. Using a threshold that is based on the selected luma element's value, similar luma values within the defined region may be identified and combined to provide a substitute value. The substitute value may be blended with the value of the selected element within the image's luma channel. In another implementation, element values from both an image's luma and chroma channels may be used to identify similar luma values.

Abstract: A system and method for denoising using signal dependent adaptive weights includes an imaging device that captures image data corresponding to a photographic target. A denoising manager identifies similar pixels from said image data that are located within a pre-defined processing window around the pixel to be denoised. The denoising manager computes signal-dependent weighting values that correspond to respective ones of the similar pixels. The denoising manager then calculates the denoised pixel value by utilizing the weighting values in conjunction with raw pixel values of the similar pixel set. In this manner all pixels in the image are denoised.

Abstract: Improving color calibration, and similar operations, by generating an optimal raw RGB color chart, in the raw RGB domain, for an imaging device with a given type of image sensor, such as for a digital still camera. Calibration is performed in response to a constraint which takes into account the spectral sensitivity of the image sensor used on the camera as well as spectral reflectance and spectral radiance of multiple illuminants. Calibration is performed using the raw RGB color chart which is illuminant independent and image sensor specific and which can match the calibration performance of known calibration standards, such as Macbeth 24.

Abstract: A system and method for effectively performing wavelet transforms on incomplete image data includes an image processor that performs a green-pixel transformation procedure on incomplete color pixel matrices. The image processor then rearranges red, blue and transformed green-pixel into four quadrants of contiguous pixels and applies some two dimensional (2D) wavelet thresholding schemes on each quadrant. After thresholding, an inverse procedure is applied to reconstruct the pixel values on the incomplete color pixel matrices. For further de-correlation of image data, the image processor may stack similar image patches in a three dimensional (3D) array and apply incomplete-data wavelet thresholding on the 3D array. The incomplete-data wavelet thresholding procedure may be put in an improved local similarity measurement framework to achieve better performance of image processing tasks. A CPU device typically controls the image processor to effectively perform the image processing procedure.

Abstract: A method for effectively performing local image similarity measurement is proposed. A system equipped with such a method for effectively performing an image processing task includes an image processor that performs an intermediate-results calculation procedure to calculate intermediate result values that are based upon corresponding pixels of a target patch and one or more similar patches. The image processor typically moves the target patch of the intermediate-results calculation to different locations in a raster order or some other organized order. The image processor then performs an intermediate-results combination procedure by calculating appropriate statistics of the intermediate result values to produce processed pixel values. A processor device typically controls the image processor to effectively perform the image processing tasks including, but not limited to, demosaicing and denoising.

Abstract: A method and apparatus for multiview image generation using depth map information is described. In one embodiment, a computer-implemented method comprises converting a input image and an input depth map into a projected image and a projected depth map using values from physical pixel locations that map to projected pixel locations, wherein the projected image and the projected depth map are associated with a particular view of the input image, inpainting the projected image and the projected depth map and producing an output image in a direction of the particular view using the inpainted projected image and the inpainted projected depth map.

Abstract: A method and apparatus for converting a two-dimensional image into a stereoscopic three-dimensional image. In one embodiment, a computer implemented method of converting a two-dimensional image into a stereoscopic three-dimensional image including for each pixel within a right eye image, identifying at least one corresponding pixel from a left eye image and determining a depth and an intensity value for the each pixel within the right eye image using the at least one corresponding pixel, wherein the depth value is stored in a right eye depth map and the intensity value is stored in the right eye image and inpainting at least one occluded region within the right eye image using the right eye depth map.

Abstract: A method and apparatus of in-painting an image using prioritized graph cut optimization is disclosed. In one embodiment, the method includes examining an image comprising a plurality of pixels that form a source region and a target region, wherein the source region comprises pixel information partitioning the source region into blocks, defining boundary areas comprising a portion of the source region and a portion of the target region, computing a plurality of energy values for the source region and the boundary areas, wherein energy values represent intensity comparisons between the boundary areas and neighboring blocks of the source region and assigning labels to the boundary areas using on a graph-cut technique, wherein each label is associated with a neighboring block and an minimal energy value for each boundary area and storing pixel information based on the pixel information of the neighboring blocks associated with the minimal energy values.

Abstract: An improved method and apparatus for localizing objects within an image is disclosed. In one embodiment, the method comprises accessing at least one object model representing visual word distributions of at least one training object within training images, detecting whether an image comprises at least one object based on the at least one object model, identifying at least one region of the image that corresponds with the at least one detected object and is associated with a minimal dissimilarity between the visual word distribution of the at least one detected object and a visual word distribution of the at least one region and coupling the at least one region with indicia of location of the at least one detected object.

Abstract: A fast accurate multi-channel frequency dependent scheme for analyzing noise in a signal processing system is described herein. Noise is decomposed within each channel into frequency bands and sub-band noise is propagated. To avoid the computational complexity of a convolution, traditional methods either assume the noise to be white, at any point in the signal processing pipeline, or they just ignore spatial operations. By assuming the noise to be white within each frequency band, it is possible to propagate any type of noise (white, colored, Gaussian, non-Gaussian and others) across a spatial transformation in a very fast and accurate manner. To demonstrate the efficacy of this technique, noise propagation is considered across various spatial operations in an image processing pipeline. Furthermore, the computational complexity is a very small fraction of the computational cost of propagating an image through a signal processing system.

Abstract: Improving color calibration, and similar operations, by generating an optimal raw RGB color chart, in the raw RGB domain, for an imaging device with a given type of image sensor, such as for a digital still camera. Calibration is performed in response to a constraint which takes into account the spectral sensitivity of the image sensor used on the camera as well as spectral reflectance and spectral radiance of multiple illuminants. Calibration is performed using the raw RGB color chart which is illuminant independent and image sensor specific and which can match the calibration performance of known calibration standards, such as Macbeth 24.

Abstract: A method of adaptive local image similarity measurement based on the L1 distance measure is described. A relationship between distance measures is used to estimate appropriate thresholds for various patch sizes. The choice of patch size depends on the degradations contained in the image and the application. The relation between the similarity measures is established using the distribution of L1 distances for various patch sizes. For larger degradations, similarity measure with a bigger patch size is employed. For lesser imperfections, a smaller patch size produces acceptable results. To keep the computational overhead manageable, the smallest patch size that gives the desired image quality is employed.