Abstract: A noise reduction apparatus for digital cameras is presented that includes groups of one or more connected non-linear filter units. Each of the filter unit groups are driven by decimated input image data at a different level of decimation and the output of at least one of these filter unit groups serves as one of a plurality of inputs to another filter unit group driven at a different decimation level. Filtered image data from one or more filter unit groups is adaptively combined in response to one or more image metrics related to one or more local regional image characteristics.

Abstract: A noise reduction apparatus for digital cameras is presented that includes groups of one or more connected non-linear filter units. Each of the filter unit groups are driven by decimated input image data at a different level of decimation and the output of at least one of these filter unit groups serves as one of a plurality of inputs to another filter unit group driven at a different decimation level. Filtered image data from one or more filter unit groups is adaptively combined in response to one or more image metrics related to one or more local regional image characteristics.

Abstract: A noise reduction apparatus for digital cameras is presented that includes groups of one or more connected non-linear filter units. Each of the filter unit groups are driven by decimated input image data at a different level of decimation and the output of at least one of these filter unit groups serves as one of a plurality of inputs to another filter unit group driven at a different decimation level. Filtered image data from one or more filter unit groups is adaptively combined in response to one or more image metrics related to one or more local regional image characteristics.

Abstract: Methods and the corresponding device are presented for the correction of lateral chromatic aberration within a digital camera or other imaging device, using calibration approaches that do not require previously acquired lens data to effect the correction. An in-camera auto-calibration procedure is performed on the attached lens, such as when a lens is exchanged, and extracts parameters required for chromatic aberration correction, respecting zoom and focus, from one or more captured images. Based on image data extracted as a plurality of channels of a chromatic decomposition of the image, the chromatic aberration information for the lens is extracted. From the chromatic aberration information, the correction factors for the lens are determined.

Abstract: A system, method, and computer program product for automatically detecting and correcting the “purple fringing” effect, typically due to axial chromatic aberration in imaging devices, are disclosed and claimed. A chromaticity score is computed, denoting the amount of false color related to a purple fringing artifact. A locality score is computed, denoting the similarity of the purple fringing region to a shape of a narrow ridge, which is typical for purple fringing artifacts. A saturation score is also computed, denoting the proximity of a pixel to saturated pixels. These scores are then combined into a detection score, denoting pixels having strong indications they share properties common to pixels of purple fringing artifacts. The detected pixels are then correspondingly corrected, e.g. by chroma suppression. The scoring and correction may be performed over combinations of image resolutions, e.g. an original version and potentially numerous downscaled versions.

Abstract: A system, method, and computer program product for automatically detecting and correcting the “purple fringing” effect, typically due to axial chromatic aberration in imaging devices, are disclosed and claimed. A chromaticity score is computed, denoting the amount of false color related to a purple fringing artifact. A locality score is computed, denoting the similarity of the purple fringing region to a shape of a narrow ridge, which is typical for purple fringing artifacts. A saturation score is also computed, denoting the proximity of a pixel to saturated pixels. These scores are then combined into a detection score, denoting pixels having strong indications they share properties common to pixels of purple fringing artifacts. The detected pixels are then correspondingly corrected, e.g. by chroma suppression. The scoring and correction may be performed over combinations of image resolutions, e.g. an original version and potentially numerous downscaled versions.

Abstract: A system, method, and computer program product for automatically detecting and correcting the “purple fringing” effect, typically due to axial chromatic aberration in imaging devices, are disclosed and claimed. A chromaticity score is computed, denoting the amount of false color related to a purple fringing artifact. A locality score is computed, denoting the similarity of the purple fringing region to a shape of a narrow ridge, which is typical for purple fringing artifacts. A saturation score is also computed, denoting the proximity of a pixel to saturated pixels. These scores are then combined into a detection score, denoting pixels having strong indications they share properties common to pixels of purple fringing artifacts. The detected pixels are then correspondingly corrected, e.g. by chroma suppression. The scoring and correction may be performed over combinations of image resolutions, e.g. an original version and potentially numerous downscaled versions.

Abstract: Methods and the corresponding device are presented for the correction of lateral chromatic aberration within a digital camera or other imaging device, using calibration approaches that do not require previously acquired lens data to effect the correction. An in-camera auto-calibration procedure is performed on the attached lens, such as when a lens is exchanged, and extracts parameters required for chromatic aberration correction, respecting zoom and focus, from one or more captured images. Based on image data extracted as a plurality of channels of a chromatic decomposition of the image, the chromatic aberration information for the lens is extracted.

Abstract: A device for noise reduction is provided. The device includes a noise reduction three-dimensional look-up table (LUT) and a noise reduction unit. The noise reduction LUT transforms an input image into a noise reduction factor and noise reduction threshold for each color component of each pixel of the input image. The noise reduction unit performs noise reduction on the input image based on the noise reduction factors and noise reduction thresholds determined from the noise reduction LUT.

Abstract: Methods and the corresponding device are presented for the correction of lateral chromatic aberration within a digital camera or other imaging device, using calibration approaches that do not require previously acquired lens data to effect the correction. An in-camera auto-calibration procedure is performed on the attached lens, such as when a lens is exchanged, and extracts parameters required for chromatic aberration correction, respecting zoom and focus, from one or more captured images. Based on image data extracted as a plurality of channels of a chromatic decomposition of the image, the chromatic aberration information for the lens is extracted. From the chromatic aberration information, the correction factors for the lens are determined.

Abstract: A noise reduction apparatus for digital cameras is presented that includes groups of one or more connected non-linear filter units. Each of the filter unit groups are driven by decimated input image data at a different level of decimation and the output of at least one of these filter unit groups serves as one of a plurality of inputs to another filter unit group driven at a different decimation level. Filtered image data from one or more filter unit groups is adaptively combined in response to one or more image metrics related to one or more local regional image characteristics.

Abstract: A noise reduction apparatus is presented that includes groups of one or more serially connected non-linear filter units. Each of the filter unit groups are driven by decimated input image data at a different level of decimation and the output of at least one of these groups serves as one of a plurality of inputs to another group driven at a different decimation level.

Abstract: Methods and corresponding apparatus are presented that perform dynamic range compensation (DRC) and noise reduction (NR) together, adjusting the noise reduction parameters in response to the dynamic range compensation decisions. By such a modification of image noise reduction parameters based on the dynamic range compensation gain or, more generally, other such factors, these techniques make it possible to perform DRC on noisy images, achieving an image with low and uniform noise levels.

Abstract: A noise reduction apparatus is presented that includes groups of one or more serially connected non-linear filter units. Each of the filter unit groups are driven by decimated input image data at a different level of decimation and the output of at least one of these groups serves as one of a plurality of inputs to another group driven at a different decimation level.

Abstract: A method and apparatus are provided for correcting image data of an image sensor. In on embodiment, a method includes receiving sensor data including image data having at least one artifact and smear sensitive data, detecting motion of one or more light sources associated with the artifact and characterizing the motion of the one or more light sources to provide a motion characteristic. The method may further include correcting at least a portion of the image data based on the smear sensitive data and the motion characteristic of the one or more light sources, wherein the correcting is responsive to vertical motion and non-vertical motion of the one or more light sources.

Abstract: Methods and corresponding apparatus are presented that perform dynamic range compensation (DRC) and noise reduction (NR) together on a pixel-by-pixel basis, adjusting the noise reduction parameters in response to the dynamic range compensation decisions. By such a modification of image noise reduction parameters based on the dynamic range compensation gain or, more generally, other such factors, these techniques make it possible to perform DRC on noisy images, achieving an image with low and uniform noise levels.

Abstract: A device for noise reduction is provided. The device includes a noise reduction three-dimensional look-up table (LUT) and a noise reduction unit. The noise reduction LUT transforms an input image into a noise reduction factor and noise reduction threshold for each color component of each pixel of the input image. The noise reduction unit performs noise reduction on the input image based on the noise reduction factors and noise reduction thresholds determined from the noise reduction LUT.

Abstract: Methods and the corresponding device are presented for the correction of lateral chromatic aberration within a digital camera or other imaging device, using calibration approaches that do not require previously acquired lens data to effect the correction. An in-camera auto-calibration procedure is performed on the attached lens, such as when a lens is exchanged, and extracts parameters required for chromatic aberration correction, respecting zoom and focus, from one or more captured images. Based on image data extracted as a plurality of channels of a chromatic decomposition of the image, the chromatic aberration information for the lens is extracted. From the chromatic aberration information, the correction factors for the lens are determined.

Abstract: A noise reduction apparatus is presented that includes groups of one or more serially connected non-linear filter units. Each of the filter unit groups are driven by decimated input image data at a different level of decimation and the output of at least one of these groups serves as one of a plurality of inputs to another group driven at a different decimation level.

Abstract: Methods and corresponding apparatus are presented that perform digital range compensation (DRC) and noise reduction (NR) together, adjusting the noise reduction parameters in response to the digital range compensation decisions. By such a modification of image noise reduction parameters based on the dynamic range compensation gain or, more generally, other such factors, these techniques make it possible to perform DRC on noisy images, achieving an image with low and uniform noise levels.