Abstract: An embodiment method for estimating a missing or incorrect value in a table of values generated by a photosite matrix comprises a definition of a zone of the table comprising the value to be estimated and other values, referred to as neighboring values, and an estimation of the value to be estimated based on the primary neighboring values and the weight associated with these primary neighboring values, wherein a weight of each neighboring value, referred to as primary neighboring value, of the same colorimetric component as that of the missing or incorrect value to be estimated, is determined according to differences between neighboring values disposed on an axis and neighboring values disposed parallel with this axis and positioned in relation to this axis on the same side as the primary neighboring value for which the weight is determined.

Abstract: An indirect time-of-flight measurement sensor includes a photosensitive pixel array configured to acquire a succession of images of a scene during a given exposure time. The sensor includes a control unit configured to control the acquisition of the succession of images by the pixel array and to define an exposure time for this acquisition based on a pixel saturation rate of the array, distances between the sensor and elements of the scene, and a standard deviation of the distances between the sensor and the elements of the scene.

Abstract: An embodiment method for estimating a missing or incorrect value in a table of values generated by a photosite matrix comprises a definition of a zone of the table comprising the value to be estimated and other values, referred to as neighboring values, and an estimation of the value to be estimated based on the primary neighboring values and the weight associated with these primary neighboring values, wherein a weight of each neighboring value, referred to as primary neighboring value, of the same colorimetric component as that of the missing or incorrect value to be estimated, is determined according to differences between neighboring values disposed on an axis and neighboring values disposed parallel with this axis and positioned in relation to this axis on the same side as the primary neighboring value for which the weight is determined.

Abstract: In an embodiment an apparatus includes a scanning photographic sensor configured to acquire an image, according to an integration time of the sensor, of a scene illuminated with periodically emitted light pulses by a source, so that the image has a regular succession of bands with different luminosities when the integration time of the sensor is different from a period of the light pulses, a processor configured to generate a signature vector representative of the regular succession of bands with different luminosities being present in the image acquired by the photographic sensor, wherein the signature vector is independent of a reflectance of an objects of the scene and of a level of light in the scene, determine a frequency of the bands in the image on basis of the generated signature vector and determine the period of the pulses of the source on basis of the determined frequency of the bands in the image, and a controller configured to adjust the integration time of the photographic sensor so that the int

Abstract: An embodiment method for estimating a missing or incorrect value in a table of values generated by a photosite matrix comprises a definition of a zone of the table comprising the value to be estimated and other values, referred to as neighboring values, and an estimation of the value to be estimated based on the primary neighboring values and the weight associated with these primary neighboring values, wherein a weight of each neighboring value, referred to as primary neighboring value, of the same colorimetric component as that of the missing or incorrect value to be estimated, is determined according to differences between neighboring values disposed on an axis and neighboring values disposed parallel with this axis and positioned in relation to this axis on the same side as the primary neighboring value for which the weight is determined.

Abstract: A system has an array of pixels including a plurality of active pixels and a plurality of dark reference pixels and processing circuitry coupled to the array of pixels. The processing circuitry sequentially computes, for each of a plurality of pairs of sets of dark reference pixels of the plurality of dark reference pixels, absolute differences in dark signal levels of the pair of sets of dark reference pixels. The absolute differences in dark signal levels are accumulated and a noise level of the dark reference pixels of the array of pixels is estimated based on the accumulated absolute differences. The system may be employed in, for example, a back-up camera of an automobile or a mobile phone.

Abstract: A system has an array of pixels including a plurality of active pixels and a plurality of dark reference pixels and processing circuitry coupled to the array of pixels. The processing circuitry sequentially computes, for each of a plurality of pairs of sets of dark reference pixels of the plurality of dark reference pixels, absolute differences in dark signal levels of the pair of sets of dark reference pixels. The absolute differences in dark signal levels are accumulated and a noise level of the dark reference pixels of the array of pixels is estimated based on the accumulated absolute differences. The system may be employed in, for example, a back-up camera of an automobile or a mobile phone.

Abstract: Various embodiments provide an optimized image filter. The optimized image and video obtains an input image and selects a target pixel for modification. Difference values are then determined between the selected target pixel and each reference pixel of a search area. Subsequently, a weighting function is used to determine weight values for each of the reference pixels of the search area based on their respective difference value. The selected target pixel is then modified by the optimized image filter using the determined weight values. A new target pixel in an apply patch is then selected for modification. The new target pixel is modified using the previously determined weight values reassigned to a new set of reference pixels. The previously determined weight values are reassigned to the new set of reference pixels based on each of the new set of reference pixels' position relative to the new target pixel.

Abstract: Various embodiments provide an optimized image filter. The optimized image and video obtains an input image and selects a target pixel for modification. Difference values are then determined between the selected target pixel and each reference pixel of a search area. Subsequently, a weighting function is used to determine weight values for each of the reference pixels of the search area based on their respective difference value. The selected target pixel is then modified by the optimized image filter using the determined weight values. A new target pixel in an apply patch is then selected for modification. The new target pixel is modified using the previously determined weight values reassigned to a new set of reference pixels. The previously determined weight values are reassigned to the new set of reference pixels based on each of the new set of reference pixels' position relative to the new target pixel.

Abstract: Various embodiments provide an optimized image filter. The optimized image and video obtains an input image and selects a target pixel for modification. Difference values are then determined between the selected target pixel and each reference pixel of a search area. Subsequently, a weighting function is used to determine weight values for each of the reference pixels of the search area based on their respective difference value. The selected target pixel is then modified by the optimized image filter using the determined weight values. A new target pixel in an apply patch is then selected for modification. The new target pixel is modified using the previously determined weight values reassigned to a new set of reference pixels. The previously determined weight values are reassigned to the new set of reference pixels based on each of the new set of reference pixels' position relative to the new target pixel.

Abstract: Various embodiments provide an optimized image filter. The optimized image and video obtains an input image and selects a target pixel for modification. Difference values are then determined between the selected target pixel and each reference pixel of a search area. Subsequently, a weighting function is used to determine weight values for each of the reference pixels of the search area based on their respective difference value. The selected target pixel is then modified by the optimized image filter using the determined weight values. A new target pixel in an apply patch is then selected for modification. The new target pixel is modified using the previously determined weight values reassigned to a new set of reference pixels. The previously determined weight values are reassigned to the new set of reference pixels based on each of the new set of reference pixels' position relative to the new target pixel.

Abstract: A method of generating first and second panoramic pictures based on a series of frames acquired by a frame acquisition device is provided. While the device is panned in a main direction, a global motion value reflecting a displacement in the main direction between consecutive frames and a perspective transform reflecting a perspective change between the frames are computed. For each frame, a first area of the frame is determined for the first panoramic picture and a second area of the frame, distinct from the first area, is determined for the second panoramic picture. An adapted first area is determined by applying an inverse of the global transform to the first area of the current frame, the adapted first area being included into the first panoramic picture and the second area of the current frame being included into the second panoramic picture.

Abstract: An apparatus for calibrating a stereoscopic camera with respect to at least one stereo-image of the stereoscopic camera includes a processing unit configured to support at least a first triangulation unit, a second triangulation unit, and a Bundle Adjustment unit. The processing unit is configured to determine whether a convergence criterion has been met, the convergence criterion being indicative of whether or not a camera calibration ground-truth has been found.

Abstract: It is provided a method implemented by an electronic device for image mosaicing. The method comprises providing a mosaic and an image, wherein the mosaic and the image each represent at least part of a scene. The method also comprises estimating a motion of blocks of the image, wherein the motion of a given block of a given image represents how the scene content of the given block has moved during a time interval before taking the given image. The method then comprises integrating part of the image to the mosaic according to the estimation. Such a method improves the way of performing image mosaicing.

Abstract: There is described a method and a device for forming a panoramic image wherein it is decided to add a current image in a current panoramic image based on definitions of edges of the current image and the current panoramic image.

Abstract: The invention concerns a method of generating at least a first panoramic picture and a second panoramic picture based on a series of frames acquired by one frame acquisition device while said device is panned in a main direction, a global motion value and a perspective transform being computed for each pair of consecutive frames of the series, the global motion value reflecting a displacement in the main direction between the frames of a pair of frames and the perspective transform reflecting a perspective change between the frames of a pair of frames. For each frame of the series, a first area of the frame is determined for the first panoramic picture and a second area of the frame, distinct from the first area, is determined for the second panoramic picture.

Abstract: It is provided a method implemented by an electronic device for image mosaicing. The method comprises providing a mosaic and an image, wherein the mosaic and the image each represent at least part of a scene. The method also comprises estimating a motion of blocks of the image, wherein the motion of a given block of a given image represents how the scene content of the given block has moved during a time interval before taking the given image. The method then comprises integrating part of the image to the mosaic according to the estimation. Such a method improves the way of performing image mosaicing.

Abstract: There is described a method and a device for forming a panoramic image wherein it is decided to add a current image in a current panoramic image based on definitions of edges of the current image and the current panoramic image.

Abstract: A processing device (D) is dedicated to image frame stabilization of digital video sequences in an electronic equipment (E1), such as a digital camera, for instance. This processing device (D) comprises processing means (PM) arranged, for each current image frame of a video sequence, for determining a type of motion present in the video sequence from global motion parameters of the current image frame and the ones of at least one preceding image frame of this video sequence. These parameters are determined from a motion estimation between the current image frame and the preceding one of the video sequence. The motion determination is followed by a selection of a jitter extraction technique amongst at least two jitter extraction techniques depending on this determined motion type. The jitter extraction technique thus chosen is used to determine a jitter intended to be removed from the determined global motion parameter(s) in order to remove unwanted motion(s) present into the current image frame.

Abstract: A processing device (D) is dedicated to image frame stabilization of digital video sequences in an electronic equipment (E1), such as a digital camera, for instance. This processing device (D) comprises processing means (PM) arranged, for each current image frame of a video sequence, for determining a type of motion present in the video sequence from global motion parameters of the current image frame and the ones of at least one preceding image frame of this video sequence. These parameters are determined from a motion estimation between the current image frame and the preceding one of the video sequence. The motion determination is followed by a selection of a jitter extraction technique amongst at least two jitter extraction techniques depending on this determined motion type. The jitter extraction technique thus chosen is used to determine a jitter intended to be removed from the determined global motion parameter(s) in order to remove unwanted motion(s) present into the current image frame.