Abstract: A method for associating with a digital image a class of a plurality of predefined classes having respective models, the method including the phases of dividing the digital image pixel by pixel into one or more regions belonging to a set of predefined regions that differ from each other on account of their type of content, the division being effected by establishing whether or not a pixel of the image belongs to a respective region on the basis of an operation of analyzing the parameters this pixel, the analysis operation being carried out by verifying that the parameters satisfy predefined conditions and/or logico-mathematical relationships of belonging to the respective region, acquiring from the digital image divided into regions information regarding the regions that are present in it, comparing this information with at least one model characterizing a respective class of said plurality, and associating with the digital image a class on the basis of the comparison phase.

Abstract: A method of processing digital video signals produced by a sensor that are to be presented on a viewfinder, the method involving: a first pair of processing operations for scaling and color interpolation; and a second pair of processing operations for the formation of a color matrix and for white balancing. The operations of at least one, and preferably of both of the pairs of processing operations are executed in a single step. The operation of white balancing is moreover performed only for one frame out of K frame in the frame sequence. The preferential application is in the construction of viewfinders for videocameras and digital still cameras.

Abstract: A method for compression includes applying a discrete cosine transform to said image data to obtain transform coefficients, quantizing the transform coefficients by applying a quantization level scaled through a gain value, adjusting the gain value as a function of desired image parameters by executing a first time said quantization operation applying a first gain value and obtaining first quantized data, estimating statistically a second gain value suitable to obtain the desired image parameters, and executing a second time said quantization operation applying said second gain value. The operation of statistical estimation of the second gain value includes evaluating a threshold value as a function of the desired image parameters and setting to zero a percentage of coefficients of the first quantized data as a function of the threshold value.

Abstract: A raster to vector conversion method of an initial digital image including a pixel matrix, includes generating a digital image divided into polygons by dividing the initial digital image into a plurality of base triangles and defining similarity criteria depending on at least one parameter. The conversion method also includes an iterative operation to process the digital image divided into polygons, selecting pairs of polygons adjacent to each other and to satisfy the similarity criteria and merging together the selected polygons.

Abstract: In the method, the membership image is produced through a multi-stage process that contemplates a first punctual classification stage generating a rough membership image, followed by a low-pass filtering of regionalization of the image through a down-sampling of the image followed by an up-sampling of the image, and in a further step of merging the regions that overcomes the superposition effects induced by the low-pass filtering operation. The so generated membership image contains semantic information of the input image that may be used for effectively implementing an adaptive correction/improvement of the color of the input image. For an adaptive correction/improvement of the color, the encoded data of the generated membership image is fed in parallel to the data of the real image to an adaptive modification block of the color of the image pixels.

Abstract: A method of compressing digital images acquired in CFA format that utilizes optimized quantization matrices. The method, basing itself on the statistical characterization of the error introduced during the processing phase that precedes compression, appropriately modifies the coefficients of any initial quantization matrix, even of a standard type, obtaining a greater compression efficiency without introducing further quality losses.

Abstract: A digital image processing method includes extracting chromatic information of an image taken by an image taking device and related to a human subject; detecting visually interesting regions; and exposure correcting of the taken image by normalizing a grey scale of the taken image based on the visually interesting regions. Advantageously, the method includes recognizing areas corresponding to the skin of the subject, these areas being used as the visually interesting regions for the exposure correction step.

Abstract: A method for obtaining a high-resolution digital image from a plurality of starting images formed by pixel matrices acquired at a lower resolution includes combining the plurality of starting images to generate a provisional high-resolution image, and producing from the provisional high-resolution image a plurality of low-resolution images. Each low-resolution image corresponds to a respective starting image. At least a portion of the provisional high-resolution image is processed by modifying pixels thereof to reduce a difference between the plurality of starting images and the plurality of low-resolution images. The processing includes associating with the pixels of the provisional high-resolution image a respective uncertainty measure representing an uncertainty of the pixels, and leaving unmodified at least a subset of the pixels of the provisional high-resolution image having associated therewith a respective uncertainty measure smaller than a threshold.

Abstract: A method of compressing digital images acquired in CFA format that utilizes optimized quantization matrices. The method, basing itself on the statistical characterization of the error introduced during the processing phase that precedes compression, appropriately modifies the coefficients of any initial quantization matrix, even of a standard type, obtaining a greater compression efficiency without introducing further quality losses.

Abstract: A method for obtaining a high resolution digital image from a plurality of starting images formed by pixel matrices and acquired at a lower resolution is provided. The method may include combining the plurality of starting images to generate a provisional high resolution image formed by a pixel matrix. The method may also include associating a respective error with at least a part of the pixels of the provisional image HR(0). More particularly, this may include providing a first error associated with at least one first pixel, and at least partially processing the provisional image by modifying the pixels of this image based upon the respective errors associated therewith. A second error may also be calculated to associate with at least one second pixel situated in the vicinity of the first pixel in the matrix (HR(0)). The second error may be calculated by using the first error associated with the at least one first pixel.

Abstract: A method for improving the quality of a digital image acquired with a non-optimal exposure. In one embodiment, the method, which is applied directly to the image in CFA (Color Filter Array) format, identifies the regions of the image that are most important from the perceptive or contextual point of view by means of simple statistical measures. The image is then transformed by inverting the response function in such a manner as to optimize the quality of these regions.

Abstract: A method of compressing digital images acquired in CFA format that utilizes optimized quantization matrices. The method, basing itself on the statistical characterization of the error introduced during the processing phase that precedes compression, appropriately modifies the coefficients of any initial quantization matrix, even of a standard type, obtaining a greater compression efficiency without introducing further quality losses.

Abstract: A method of processing digital source images, each represented by pixel matrices, to obtain from two or more source images, representing one and the same real scene and acquired by utilizing different exposure levels, a final digital image capable of reproducing the real scene with an exposure latitude greater than that of each of the source images. The method, which can be advantageously used in digital still cameras, produces the final image by combining the source images with the help of a weighted average constructed pixel by pixel. Thanks to a special filtering to which the weighting coefficients are subjected before the weighted mean operation, the method obtains a final image in which the source images are harmoniously combined with each other.

Abstract: A method of processing digital source images, each represented by pixel matrices, to obtain from two or more source images, representing one and the same real scene and acquired by utilizing different exposure levels, a final digital image capable of reproducing the real scene with an exposure latitude greater than that of each of the source images. The method, which can be advantageously used in digital still cameras, produces the final image by combining the source images with the help of a weighted average constructed pixel by pixel. Thanks to a special filtering to which the weighting coefficients are subjected before the weighted mean operation, the method obtains a final image in which the source images are harmoniously combined with each other.

Abstract: A method for compression includes applying a discrete cosine transform to said image data to obtain transform coefficients, quantizing the transform coefficients by applying a quantization level scaled through a gain value, adjusting the gain value as a function of desired image parameters by executing a first time said quantization operation applying a first gain value and obtaining first quantized data, estimating statistically a second gain value suitable to obtain the desired image parameters, and executing a second time said quantization operation applying said second gain value. The operation of statistical estimation of the second gain value includes evaluating a threshold value as a function of the desired image parameters and setting to zero a percentage of coefficients of the first quantized data as a function of the threshold value.

Abstract: A method for transforming a matrix representation of pixels of an image into a vector representation of the image involves partition of the image into contiguous homogeneous regions by applying a watershed type morphologic algorithm to the matrix representation of pixels and identifying the contours of the contiguous homogeneous regions by applying a vector code contouring algorithm of the chain-code type to every region. By selecting quantization level of the gradient, improved image quality, dimensions and noise are achieved.

Abstract: A raster to vector conversion method of an initial digital image including a pixel matrix, includes generating a digital image divided into polygons by dividing the initial digital image into a plurality of base triangles and defining similarity criteria depending on at least one parameter. The conversion method also includes an iterative operation to process the digital image divided into polygons, selecting pairs of polygons adjacent to each other and to satisfy the similarity criteria and merging together the selected polygons.

Abstract: In the method, the membership image is produced through a multi-stage process that contemplates a first punctual classification stage generating a rough membership image, followed by a low-pass filtering of regionalization of the image through a down-sampling of the image followed by an up-sampling of the image, and in a further step of merging the regions that overcomes the superposition effects induced by the low-pass filtering operation. The so generated membership image contains semantic information of the input image that may be used for effectively implementing an adaptive correction/improvement of the color of the input image. For an adaptive correction/improvement of the color, the encoded data of the generated membership image is fed in parallel to the data of the real image to an adaptive modification block of the color of the image pixels.

Abstract: A method for associating with a digital image a class of a plurality of predefined classes having respective models, the method including the phases of dividing the digital image pixel by pixel into one or more regions belonging to a set of predefined regions that differ from each other on account of their type of content, the division being effected by establishing whether or not a pixel of the image belongs to a respective region on the basis of an operation of analyzing the parameters this pixel, the analysis operation being carried out by verifying that the parameters satisfy predefined conditions and/or logico-mathematical relationships of belonging to the respective region, acquiring from the digital image divided into regions information regarding the regions that are present in it, comparing this information with at least one model characterizing a respective class of said plurality, and associating with the digital image a class on the basis of the comparison phase.

Abstract: A method of obtaining a depth map from a single digital image of a three-dimensional scene containing geometric objects is provided that includes the identification in the image of at least one horizontal plane or one vertical plane of the three-dimensional scene and the assignment to every point of the image forming part of the identified plane, or to each one of the identified planes, of a depth level according to its distance from, respectively, a predetermined horizontal or vertical reference straight line of the image. In particular, the identification of at least one plane includes the identification in the image of at least two vanishing lines corresponding to two parallel lines in the plane and the assignment of a depth level made in accordance with the angular coefficients of the identified vanishing lines. Also included is a completely automatic method for obtaining a depth map from a single digital image of any three-dimensional scene.