Abstract: Certain aspects relate to systems and techniques for correction of color artifacts including both color aberration and color spot artifacts using a unified framework. For example, both color aberration and color spot artifacts can be corrected using a post-processing method implementing directional median filtering on chroma channels. A pixel-by-pixel correction ratio map can be built by analyzing the luma and chroma components of the image to indicate a type of color artifact associated with each pixel in the image, and a directional median filter can be selected for each pixel based on the corresponding correction ratio map value.

Abstract: Systems and methods for reducing noise artifacts in an image are disclosed. A radial distance-based look up table may be used to calibrate a noise property change due to the vignette effect. Based on the look up table, a spatial varying noise reduction level is computed to correct the noise property distortion due to the image vignetting.

Abstract: Embodiments include a method of image processing including decomposing a reflectance spectrum for a test surface into a linear combination of reflectance spectra of a set of test targets. The coefficient vector calculated in this decomposition is used to predict a response of an imaging sensor to the test surface. A plurality of such predicted responses may be used for various applications involving color detection and/or classification, including human skin tone detection.

Abstract: Systems, methods and apparatus for image processing by classifying pixels are described. In some systems, an exposure control operation is performed according to the pixel classifications. In some cases, the pixels are classified according to a predetermined segmentation of a color space, based on predicted sensor responses.

Abstract: This disclosure describes techniques for initially calibrating an image capture device. According to one aspect, the calibration includes calibrating parameters of an image filter for resolving the captured image. The method includes receiving a captured image of a test target and resolving the captured image using a set of initial parameters. A sharpness index of the resolved image is determined without matching the captured image to the test target. The sharpness index is used to minimize a cost function for determining parameters for use by the image capture device.

Abstract: Techniques are described for automatic print image matching (PIM) parameter extraction. An original image is captured and PIM parameter data is extracted automatically based on specifics of the original image. At least one automated PIM parameter is calculated automatically from the PIM parameter data. At least one automated PIM parameter is inserted in PIM header information for communication to a rendering device to modify the original image when rendered.

Abstract: This disclosure describes barcode scanning techniques for an image capture device. The image capture device may automatically detect a barcode within an image while the image capture device is operating in a non-barcode image capture mode, such a default image capture mode. In one aspect, the detection of the barcode within the image may be based on a combination of identified edges and low intensity regions within the image. The image capture device may configure, based on the detection of the barcode, one or more image capture properties associated with the image capture device to improve a quality at which the images are captured. The image capture device captures the image in accordance with the configured image capture properties. The techniques may effectively provide a universal and integrated front-end for producing improved quality images of barcodes without requiring significant interaction with a user via a complicated user interface.

Abstract: Apparatus are provided including an image signal carrier, a luminance information evaluator, and a chrominance information modifier. The image signal carrier is encoded with an image signal including luminance information and chrominance information. The luminance information evaluator evaluates the luminance information in the image signal for a given region within the image to identify when the given region is one of substantially white and substantially dark. The chrominance information modifier is provided to modify the chrominance information corresponding to the given region when the given region is one of substantially white and substantially dark.

Abstract: The disclosure describes adaptive filtering techniques to improve the quality of captured image information, such as video or still images. An image sensor captures image information and determines a plurality of parameter values based on a current exposure index and a current scaling factor of the image information. The adaptive spatial image filter includes both horizontal and vertical sharpening filters and configures, i.e., adapts, the horizontal sharpening filter and the vertical sharpening filter based on the plurality of parameter values determined by the image sensor. The adaptive spatial image filter applies the horizontal and vertical sharpening filters to at one channel of the image information to generate filtered image information.

Abstract: This disclosure describes techniques for detecting a barcode within an image. An image processor may, for example, process an image to detect regions within the image that may be barcodes. The image processor may identify regions of the image that exhibit a high concentration of edges and a high concentration of pixels with low optical intensity co-instantaneously as potential barcodes. The image processor may identify the regions using a number of morphological operations. The image processor may then determine whether the identified regions are actually barcodes by verifying whether the region have unique barcode features. The barcode detection techniques described in this disclosure may be independent of barcode size, location and orientation within the image. Moreover, the use of morphological operations results in faster and more computationally efficient barcode detection, as well as lower computational complexity.

Abstract: This disclosure describes techniques for initially calibrating an image capture device. According to one aspect, the calibration includes calibrating parameters of an image filter for resolving the captured image. The method includes receiving a captured image of a test target and resolving the captured image using a set of initial parameters. A sharpness index of the resolved image is determined without matching the captured image to the test target. The sharpness index is used to minimize a cost function for determining parameters for use by the image capture device.

Abstract: In accordance with one embodiment of the disclosure, apparatus are provided, including an image processor, a unique image processing mechanism, and a unique image processing activation mechanism. The image processor includes the unique image processing mechanism, which processes a certain type of image. The unique image processing activation mechanism causes the unique image processing mechanism to process a given image.

Abstract: A method is disclosed that includes receiving image data and calculating brightness information of the image data. The method includes correcting at least one lens roll-off value to be used in a lens roll-off correction operation based on the brightness information. The method also includes performing the lens roll-off correction operation on the image data using the at least one corrected lens roll-off value.

Abstract: Techniques for identifying and enhancing colors in a digital image associated with one or more target color shades. In an embodiment, the target color shades may include a shade of blue associated with the sky, a shade of green associated with outdoor foliage, or the color red. In an embodiment, the blue chroma (Cb) and red chroma (Cr) coordinates of a pixel are evaluated to determine whether to apply an enhancement factor. The enhancement factor may incorporate an exposure index (EI) auxiliary enhancement factor, a color temperature (D) auxiliary enhancement factor, and a luminance (Y) of each pixel. Further aspects for implementing the techniques in software and hardware are disclosed.

Abstract: Embodiments include a method of image processing including decomposing a reflectance spectrum for a test surface into a linear combination of reflectance spectra of a set of test targets. The coefficient vector calculated in this decomposition is used to predict a response of an imaging sensor to the test surface. A plurality of such predicted responses may be used for various applications involving color detection and/or classification, including human skin tone detection.

Abstract: The disclosure is directed to techniques for region-of-interest (ROI) video processing based on low-complexity automatic ROI detection within video frames of video sequences. The low-complexity automatic ROI detection may be based on characteristics of video sensors within video communication devices. In other cases, the low-complexity automatic ROI detection may be based on motion information for a video frame and a different video frame of the video sequence. The disclosed techniques include a video processing technique capable of tuning and enhancing video sensor calibration, camera processing, ROI detection, and ROI video processing within a video communication device based on characteristics of a specific video sensor. The disclosed techniques also include a sensor-based ROI detection technique that uses video sensor statistics and camera processing side-information to improve ROI detection accuracy.

Abstract: Systems, methods and apparatus for image processing by classifying pixels are described. In some systems, an exposure control operation is performed according to the pixel classifications. In some cases, the pixels are classified according to a predetermined segmentation of a color space, based on predicted sensor responses.

Abstract: Embodiments include a method of image processing including decomposing a reflectance spectrum for a test surface into a linear combination of reflectance spectra of a set of test targets. The coefficient vector calculated in this decomposition is used to predict a response of an imaging sensor to the test surface. A plurality of such predicted responses may be used for various applications involving color detection and/or classification, including human skin tone detection.

Abstract: A camera system in normal mode and hand jitter reduction (hjr) mode may comprise generating a first exposure time-gain product by multiplying the normal mode exposure time with the normal mode gain. It may further comprise modifying the normal mode exposure time and gain and multiplying these modified parameters to generate a second exposure time-gain product for a hjr mode that reduces the difference between the first exposure time-gain product and the second exposure time-gain product. To reduce the difference the normal mode frame rate may also be modified. Operation of a camera in normal mode may be in response to a sensed light level being above a threshold. The hjr mode may be selected by the user while the camera is operating. The hjr mode may be used in response to a sensed light level being lower than the threshold.

Abstract: Systems, methods, and apparatus for image processing are described in which pixels of an image are classified according to color. In some systems, an exposure control operation is performed according to the pixel classifications. In some cases, the pixels are classified according to a color selected from among at least two colors. Systems, methods and apparatuses are also disclosed wherein luminance values are changed according to the exposure control operation.