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: 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: 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 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: 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: 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 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: There is provided a method of measuring the similarity of parts of digital image files (IF1, IF2,IF2-z)), which comprising the steps of calculating a first change value in a similarity between pixel values in a first segment (BIF1a) of a first digital image file (IF1) and in a second segment (BIF1b) of this first file (IF1), said first and second segments of said first file being spatially separated by a first translation vector (td1), calculating a second change value (v) in the similarity between pixel values in a first segment (BIF2a) of the second digital image file (IF2, IF2-z) and in a second segment (BIF2b) of the second file (IF2, IF2-z), said first and second segment of said second file being spatially separated a second translation vector (td2), wherein the first segment of the first file corresponds to substantially same part of the image as the first segment of the second file and wherein the second segment of the first file corresponds to substantially the same parts of the image as the second se

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 motion estimation method and device are provided for processing images to be inserted, between a preceding original image and a following original image, into a sequence of images. Each image is divided into pixel blocks associated with motion vectors. For a current block of an image being processed, motion vectors associated with blocks of the image being processed and/or associated with blocks of a processed image are selected. Candidate vectors are generated from selected motion vectors. An error is calculated for each candidate vector. A penalty is determined for a subset of candidate vectors on the basis of the values of the pixels of the pixel block in the preceding original image from which the candidate motion vector points to the current block and/or on the basis of the values of the pixels of the pixel block in the following original image to which the candidate motion vector points from the current block.

Abstract: A motion estimation method and device are provided for processing images to be inserted, between a preceding original image and a following original image, into a sequence of images. Each image is divided into pixel blocks associated with motion vectors. For a current block of an image being processed, motion vectors associated with blocks of the image being processed and/or associated with blocks of a processed image are selected. Candidate vectors are generated from selected motion vectors. An error is calculated for each candidate vector. A penalty is determined for a subset of candidate vectors on the basis of the values of the pixels of the pixel block in the preceding original image from which the candidate motion vector points to the current block and/or on the basis of the values of the pixels of the pixel block in the following original image to which the candidate motion vector points from the current block.

Abstract: A motion estimation method and device are provided for processing images to be inserted, between a preceding original image and a following original image, into a sequence of images. Each image is divided into pixel blocks associated with motion vectors. For a current block of an image being processed, motion vectors associated with blocks of the image being processed and/or associated with blocks of a processed image are selected. Candidate vectors are generated from selected motion vectors. An error is calculated for each candidate vector. A penalty is determined for a subset of candidate vectors on the basis of the values of the pixels of the pixel block in the preceding original image from which the candidate motion vector points to the current block and/or on the basis of the values of the pixels of the pixel block in the following original image to which the candidate motion vector points from the current block.

Abstract: There is provided a method of measuring the similarity of parts of digital image files (IF1, IF2,IF2-z)), which comprising the steps of calculating a first change value in a similarity between pixel values in a first segment (BIF1a) of a first digital image file (IF1) and in a second segment (BIF1b) of this first file (IF1), said first and second segments of said first file being spatially separated by a first translation vector (td1), calculating a second change value (v) in the similarity between pixel values in a first segment (BIF2a) of the second digital image file (IF2, IF2-z) and in a second segment (BIF2b) of the second file (IF2, IF2-z), said first and second segment of said second file being spatially separated a second translation vector (td2), wherein the first segment of the first file corresponds to substantially same part of the image as the first segment of the second file and wherein the second segment of the first file corresponds to substantially the same parts of the image as the second se

Abstract: A motion estimation method and device are provided for processing images to be inserted, between a preceding original image and a following original image, into a sequence of determined images. Each image is divided into pixel blocks and a motion vector is associated with each block of a processed image. Motion vectors associated with respective blocks of the image are processed and motion vectors associated with respective blocks of a preceding processed image (spatial and temporal motion vectors) are selected with respect to a current block of an image being processed. Candidate motion vectors are generated from the motion vectors selected. One vector is elected from among the candidate vectors. Information associating the elected vector with the block is stored. A temporal motion vector is selected only if it satisfies a determined selection criterion based on the orientation of the motion vector.

Abstract: A motion estimation method and device are provided for processing images to be inserted, between a preceding original image and a following original image, into a sequence of images. Each image is divided into pixel blocks associated with motion vectors. For a current block of an image being processed, motion vectors associated with blocks of the image being processed and/or associated with blocks of a processed image are selected. Candidate vectors are generated from selected motion vectors. An error is calculated for each candidate vector. A penalty is determined for a subset of candidate vectors on the basis of the values of the pixels of the pixel block in the preceding original image from which the candidate motion vector points to the current block and/or on the basis of the values of the pixels of the pixel block in the following original image to which the candidate motion vector points from the current block.

Abstract: A motion estimation method and device are provided for processing images to be inserted, between a preceding original image and a following original image, into a sequence of images. Each image is divided into pixel blocks associated with motion vectors. For a current block of an image being processed, motion vectors associated with blocks of the image being processed and/or associated with blocks of a processed image are selected. Candidate vectors are generated from selected motion vectors. An error is calculated for each candidate vector. A penalty is determined for a subset of candidate vectors on the basis of the values of the pixels of the pixel block in the preceding original image from which the candidate motion vector points to the current block and/or on the basis of the values of the pixels of the pixel block in the following original image to which the candidate motion vector points from the current block.

Abstract: Method and devices are provided for processing an image in which a row of pixels with associated light intensity values successively alternates with a row of pixels to which values are to be associated. In each current row of pixels with associated values, pixels are selected which satisfy a selection rule based on the values for the pixels in the current row with associated values and on the values from the previous and/or the next row with associated values, and segments of pixels are detected. In this manner a set of segments is obtained relative to the image being processed, from which a graph of segments is created by linking the segments according to a linking rule. Then the respective values to be associated with at least some of the pixels in the rows to be assigned values are determined by interpolation from segments in the graph which form a path in the graph.

Abstract: A method for detecting orientation of the contours in an image, performs an initial transformation of the image using a non-decimated multi-resolution transform, segments the image into a plurality of blocks, determines the optimal resolution for each block, and detects the predominant direction of contour for each of the blocks.