Abstract:
A method involving: detecting in an image a first type of artifact (A1) to generate a first artifact value (GA1) and a first confidence level (CA1); detecting in the image a second type of artifact (A2) to generate a second artifact value (GA2) and a second confidence level (CA2); and performing correction of the first type of artifact (A1) in the image based on the first and second artifact values (GA1, GA2) and the relative values of the first and second confidence levels (CA1, CA2).
Abstract:
A source image is transformed into a destination image having a target aspect ratio. A reference region in the source image is defined. An extended region of interest of the source image having the target aspect ratio and containing the reference region is defined. A set of candidate image regions of increasing resolutions from the extended region of interest is determined, each having the target aspect ratio and containing the reference region. Candidate image regions are scaled to form a candidate target images. A quality metric is used to select a target image providing the best quality metric value.
Abstract:
An image processing method, implemented in a calculator, includes applying a process by group of pixels to an original image. For each group of pixels, calculating a cumulative sum of value or position differences of the pixels of the group of pixels, and for each group of pixels, allocating in a final image signal a pixel position of the group of pixels to each pixel value of the group of pixels so as to minimize the cumulative sum of differences calculated for the group of pixels according to the differences calculated. For each group of pixels, determining a filtering intensity according to the cumulative sum of differences calculated for the group of pixels, and applying to the group of pixels a filtering having the filtering intensity.
Abstract:
The present description concerns a system and method of determining at least one classifier of a general movement along a first direction in video images of a scene, comprising determining a differential image based on two video images, selecting pixels of the differential image corresponding to edges of objects, determining, for each selected pixel, at least one classifier of a local movement along the first direction at least at a first or second value, determining a first indicator of the local movement along the first direction, which depends on the sum of the local movement classifiers at the first value and a second indicator of the local movement along the first direction, which depends on the sum of the local movement classifiers at the second value, and determining the general movement classifier based on the comparison of the first and second local movement indicators.
Abstract:
A method for compressing a data block including sets of homologous components may include selecting a designated component from the data block, and compressing non-designated components with a measurable loss less than or equal to a threshold. The method may further include compressing the designated component based upon at least a selection of values from among the values of the homologous designated components associated with the data of the block.
Abstract:
An image processing method, implemented in a calculator, includes applying a process by group of pixels to an original image. For each group of pixels, calculating a cumulative sum of value or position differences of the pixels of the group of pixels, and for each group of pixels, allocating in a final image signal a pixel position of the group of pixels to each pixel value of the group of pixels so as to minimize the cumulative sum of differences calculated for the group of pixels according to the differences calculated. For each group of pixels, determining a filtering intensity according to the cumulative sum of differences calculated for the group of pixels, and applying to the group of pixels a filtering having the filtering intensity.
Abstract:
A source image is transformed into a destination image having a target aspect ratio. A reference region in the source image is defined. An extended region of interest of the source image having the target aspect ratio and containing the reference region is defined. A set of candidate image regions of increasing resolutions from the extended region of interest is determined, each having the target aspect ratio and containing the reference region. Candidate image regions are scaled to form a candidate target images. A quality metric is used to select a target image providing the best quality metric value.
Abstract:
A source image is transformed into a destination image having a target aspect ratio. A reference region in the source image is defined. An extended region of interest of the source image having the target aspect ratio and containing the reference region is defined. A set of candidate image regions of increasing resolutions from the extended region of interest is determined, each having the target aspect ratio and containing the reference region. Candidate image regions are scaled to form a candidate target images. A quality metric is used to select a target image providing the best quality metric value.
Abstract:
A method involving: detecting in an image a first type of artefact (A1) to generate a first artefact value (GA1) and a first confidence level (CA1); detecting in the image a second type of artefact (A2) to generate a second artefact value (GA2) and a second confidence level (CA2); and performing correction of the first type of artefact (A1) in the image based on the first and second artefact values (GA1, GA2) and the relative values of the first and second confidence levels (CA1, CA2).
Abstract:
A source image is transformed into a destination image having a target aspect ratio. A reference region in the source image is defined. An extended region of interest of the source image having the target aspect ratio and containing the reference region is defined. A set of candidate image regions of increasing resolutions from the extended region of interest is determined, each having the target aspect ratio and containing the reference region. Candidate image regions are scaled to form a candidate target images. A quality metric is used to select a target image providing the best quality metric value.