Abstract: A system and computer-implemented method of altering perceptibility of depth in an image. The method comprises receiving a desired change in the perceptibility of depth in the image; receiving a depth-map corresponding to the image; and determining at least one characteristic of the image. The method further comprises applying an image process to the image, the image process varying in strength according to the depth map, and in accordance with a non-linear predetermined mapping relating a strength of the applied image process to a change in the perceptibility of depth, the mapping being determined with respect to the identified characteristic.

Abstract: A system and computer-implemented method of altering perceptibility of depth in an image. The method comprises receiving a desired change in the perceptibility of depth in the image; receiving a depth-map corresponding to the image; and determining at least one characteristic of the image. The method further comprises applying an image process to the image, the image process varying in strength according to the depth map, and in accordance with a non-linear predetermined mapping relating a strength of the applied image process to a change in the perceptibility of depth, the mapping being determined with respect to the identified characteristic.

Abstract: A method of determining a saliency map (e.g., 900) for an input image (e.g., 600) is disclosed. Pre-determined data defining relative salience of image features is accessed. The input image (600) is decomposed according to the predetermined data to identify features of the input image (600) corresponding to the image features in the predetermined data. A portion of the predetermined data corresponding to a range of the identified image features is selected. A perceptual scale is determined using the selected portion of the predetermined data. The saliency map (900) for the input image using the determined perceptual scale.

Abstract: A method of identifying a subject and a distractor in a target image is disclosed. The method receives a reference image comprising image content corresponding to image content of the target image. A first saliency map, which defines a distribution of visual attraction values identifying salient regions within the target image, and a second saliency map, which defines a distribution of visual attraction values identifying salient regions within the reference image, are determined. The method compares image content in salient regions of the first saliency map and the second saliency map. The subject is identified by a salient region of the target image sharing image content with a salient region of the reference image. The distractor is identified based on at least one remaining salient region of the target image.

Abstract: A method of identifying a distracting element in an image (e.g., 1100), is disclosed. A visual attention map (e.g., 1120) is determined for the image (1100), the visual attention map (1120) representing one or more regions of the image, at least one of the regions corresponding to at least a portion of a subject of the image. A salient region map (e.g., 1110) is determined for the image (1100), the salient region map comprising a distribution of visual attraction values defining one or more further regions of the image (1100), the one or more further regions being categorized as salient. An intersection between the visual attention map (1120) and the salient region map (1110) is determined to identify a distracting element in the image (1100). The distracting element corresponds to at least one of the salient regions.

Abstract: In a method of chromagenic illuminant estimation pixels from mutually-corresponding images with different filtering are compared, a fraction of the brightest pixels being selected for a subsequent chromagenic estimation. The pixels may be at corresponding locations or they may correspond in that their mean brightness is in the same rank order. In one method, in which, in a first preprocessing stage, for a database of m lights Ei(?) and n surfaces Sj(?) there is calculated Ti˜QFQ+ where Q1F and QF represent the matrices of unfiltered and filtered sensor responses to the n surfaces under the i th light and + denotes an inverse, and in a second operation stage, given P surfaces in an image and 3×P matrices Q and QF, from these matrices there are chosen the r % brightest pixels giving the matrices Q? and Q?F, and the scene illuminant Pest is estimated where formula (I) and (II).

Abstract: An image having m light sources, with m preferably equaling 2 or 3, is segmented into different regions, each of which is lit by only one of the m light sources, by obtaining paired imaged with different filtering, for example a filtered and an unfiltered image, applying to the image pairs sets of m pre-computed mappings at the pixel or region level, and selecting the most appropriate. The rendering of the information in the image maybe adjusted accordingly.

Abstract: The present invention aims to capture two images simultaneously in the visible part of the spectrum and a NIR image. This is achieved through a camera for simultaneously capturing a visible and near-infrared image by at least a sensor producing sensor response data and having at least one color filter array (CFA) comprising at least four different filters, said color filter array having visible and near-infrared light filters, and said camera comprising means to obtain a visible image while using the sensor response data from the visible part of the spectrum and a NIR image using the sensor response data from the near-infrared part of the spectrum.

Abstract: An image having m light sources, with m preferably equaling 2 or 3, is sequenced into different regions, each of which is lit by only one of the m light sources, by obtaining paired imaged with different filtering, for example a filtered and an unfiltered image, applying to the image pairs sets of m pre-computed mappings at the pixel or region level, and selecting the most appropriate. The rendering of the information in the image maybe adjusted accordingly.

Abstract: In a method of chromagenic illuminant estimation pixels from mutually-corresponding images with different filtering (e.g. a filtered image and an unfiltered image) are compared, a fraction of the brightest pixels being selected for a subsequent chromagenic estimation. The pixels may be at corresponding locations or they may correspond in that their mean brightness is in the same rank order. In one method, in which, in a first preprocessing stage, for a database of m lights Ei (?) and n surfaces Sj (?) there is calculated Ti˜QF Q+ where Q1F and QF represent the matrices of unfiltered and filtered sensor responses to the n surfaces under the i th light and + denotes an inverse, and in a second operation stage, given P surfaces in an image and 3×P matrices Q and QF, from these matrices there are chosen the r % brightest pixels giving the matrices Q? and Q?F, and the scene illuminant Pest is estimated where formula (I) and (II).

Abstract: A method of modifying perceptual quality of an image is disclosed. For each of a plurality of predetermined attributes, distribution values are determined for that attribute. The distribution values are determined across the image. Compactness of the distribution values is determined for each of the attributes. The compactness is a measure of spatial localisation of the distribution values for the respective attribute. An attribute is selected from the plurality of predetermined attributes based on the determined compactness of the respective distribution values. The selected attribute is modified in a part of the image associated with spatially localised values, so as to modify the perceptual quality of the image. The image is stored, according to the modified attribute, in a computer readable storage medium.

Abstract: The present invention aims to capture two images simultaneously in the visible part of the spectrum and a NIR image. This is achieved through a camera for simultaneously capturing a visible and near-infrared image by at least a sensor producing sensor response data and having at least one colour filter array (CFA) comprising at least four different filters, said colour filter array having visible and near-infrared light filters, and said camera comprising means to obtain a visible image while using the sensor response data from the visible part of the spectrum and a NIR image using the sensor response data from the near-infrared part of the spectrum.

Abstract: In a method of chromagenic illuminant estimation pixels from mutually-corresponding images with different filtering (e.g. a filtered image and an unfiltered image) are compared, a fraction of the brightest pixels being selected for a subsequent chromagenic estimation. The pixels may be at corresponding locations or they may correspond in that their mean brightness is in the same rank order. In one method, in which, in a first preprocessing stage, for a database of m lights Ei (?) and n surfaces Sj (?) there is calculated Ti˜QF Q+ where Q1F and QF represent the matrices of unfiltered and filtered sensor responses to the n surfaces under the i th light and + denotes an inverse, and in a second operation stage, given P surfaces in an image and 3×P matrices Q and QF, from these matrices there are chosen the r% brightest pixels giving the matrices Q? and Q?F, and the scene illuminant Pest is estimated where formula (I) and (II).

Abstract: An image having m light sources, with m preferably equaling 2 or 3, is sequenced into different regions, each of which is lit by only one of the m light sources, by obtaining paired imaged with different filtering, for example a filtered and an unfiltered image, applying to the image pairs sets of m pre-computed mappings at the pixel or region level, and selecting the most appropriate. The rendering of the information in the image maybe adjusted accordingly.