Abstract: In one embodiment, a light sensor includes four cell arrays, one for each color of the Bayer pattern, and four lenses each focusing the light coming from the scene to be captured on a respective cell array. The lenses are oriented such that at least a second green image, commonly provided by the fourth cell array, is both horizontally and vertically shifted (spaced) apart by half a pixel pitch from a first (reference) green image. In a second embodiment, the four lenses are oriented such that the red and blue images are respectively shifted (spaced) apart by half a pixel pitch from the first or reference green image, one horizontally and the other vertically, and the second green image is shifted (spaced) apart by half a pixel pitch from the reference green image both horizontally and vertically.

Abstract: In one embodiment, a light sensor includes four cell arrays, one for each color of the Bayer pattern, and four lenses each focusing the light coming from the scene to be captured on a respective cell array. The lenses are oriented such that at least a second green image, commonly provided by the fourth cell array, is both horizontally and vertically shifted (spaced) apart by half a pixel pitch from a first (reference) green image. In a second embodiment, the four lenses are oriented such that the red and blue images are respectively shifted (spaced) apart by half a pixel pitch from the first or reference green image, one horizontally and the other vertically, and the second green image is shifted (spaced) apart by half a pixel pitch from the reference green image both horizontally and vertically.

Abstract: Processing method of a digital image to filter red and/or golden eye artifacts, the digital image comprising a plurality of pixel each comprising at least one digital value represented on a plurality of bits, the method comprising: a step of selecting at least one patch of pixels of the digital image comprising pixels potentially representative of a red and/or golden eye artifact; a step of classifying the at least one patch of pixels as “eye” or “non-eye”; a step of filtering said potentially representative pixels if said patch of pixels is classified as “eye”; wherein the classifying step comprises the operations of: converting the digital values of said patch of pixels into a Gray Code representation, overall obtaining a plurality of bit maps from said patch of pixels, each bit map being associated with a respective bit of said Gray Code; an operation of individually comparing said bit maps with corresponding bit map models belonging to a patch classifier produced by a statistical analysis of bit maps obta

Abstract: In one embodiment, a light sensor includes four cell arrays, one for each color of the Bayer pattern, and four lenses each focusing the light coming from the scene to be captured on a respective cell array. The lenses are oriented such that at least a second green image, commonly provided by the fourth cell array, is both horizontally and vertically shifted (spaced) apart by half a pixel pitch from a first (reference) green image. In a second embodiment, the four lenses are oriented such that the red and blue images are respectively shifted (spaced) apart by half a pixel pitch from the first or reference green image, one horizontally and the other vertically, and the second green image is shifted (spaced) apart by half a pixel pitch from the reference green image both horizontally and vertically.

Abstract: A method calculates statistical parameters in function of stochastic momentums of the pixel intensities of a same primary color or complementary hue of a first working window (2k+1)×(2k+1), and of at least a second working window of smaller size, both centered on the pixel to be filtered and in choosing, as a function of the values of these statistical parameters, for each pixel of the color image to be filtered, the most appropriate filtering algorithm for enhancing as much as possible the contour sharpness and reducing noise and artifacts.

Abstract: Processing method of a digital image to filter red and/or golden eye artifacts, the digital image comprising a plurality of pixel each comprising at least one digital value represented on a plurality of bits, the method comprising: a step of selecting at least one patch of pixels of the digital image comprising pixels potentially representative of a red and/or golden eye artifact; a step of classifying the at least one patch of pixels as “eye” or “non-eye”; a step of filtering said potentially representative pixels if said patch of pixels is classified as “eye”; wherein the classifying step comprises the operations of: converting the digital values of said patch of pixels into a Gray Code representation, overall obtaining a plurality of bit maps from said patch of pixels, each bit map being associated with a respective bit of said Gray Code; an operation of individually comparing said bit maps with corresponding bit map models belonging to a patch classifier produced by a statistical analysis of bit maps obta

Abstract: Color image signals, as derived, e.g., by interpolating the output from a color filter array are arranged in pixels, each pixel having associated detected color information for a first color as well as undetected filled-in color information for at least a second and a third color. The images are thus exposed to false color and zipper effect artifacts, and are subject to processing preferably including the steps of: checking the images for the presence of zipper effect artifacts, and i) if the checking reveals the presence of zipper effect artifacts, applying a zipper effect removal process to the image signals; ii) if the checking fails to reveal the presence of zipper effect artifacts, applying a false color removal process to the image signals. False color and zipper effect artifacts are thus preferably both reduced by adaptively using the zipper effect removal process and the false color removal process.

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: In one embodiment, a light sensor includes four cell arrays, one for each color of the Bayer pattern, and four lenses each focusing the light coming from the scene to be captured on a respective cell array. The lenses are oriented such that at least a second green image, commonly provided by the fourth cell array, is both horizontally and vertically shifted (spaced) apart by half a pixel pitch from a first (reference) green image. In a second embodiment, the four lenses are oriented such that the red and blue images are respectively shifted (spaced) apart by half a pixel pitch from the first or reference green image, one horizontally and the other vertically, and the second green image is shifted (spaced) apart by half a pixel pitch from the reference green image both horizontally and vertically.

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: A method calculates statistical parameters in function of stochastic momentums of the pixel intensities of a same primary color or complementary hue of a first working window (2k+1)×(2k+1), and of at least a second working window of smaller size, both centered on the pixel to be filtered and in choosing, as a function of the values of these statistical parameters, for each pixel of the color image to be filtered, the most appropriate filtering algorithm for enhancing as much as possible the contour sharpness and reducing noise and artifacts.

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 fast method of color interpolation of pixels of an image acquired by a color filtered digital sensor uses a very simple cost function that nevertheless produce interpolated images of good quality. The cost function is computationally simpler because it does not require the calculation of powers and square roots. The triangulation algorithm may be executed in far less time, while practically ensuring the same performance. The triangulation algorithm on average may use only two iteration steps. The interpolation process may be followed by an anti-aliasing processing that effectively removes color artifacts.

Abstract: Subdivision per basic color channels of grey level data generated by a color sensor is no longer required according to a novel color interpolation method of an image acquired by a digital color sensor generating grey levels for each image pixel as a function of the filter applied to the sensor by interpolating the values of missing colors of each image pixel for generating triplets or pairs of values of primary colors or complementary base hues for each image pixel. The method may include calculating spatial variation gradients of primary colors or complementary base hues for each image pixel and storing the information of directional variation of primary color or complementary base hue in look-up tables pertaining to each pixel.

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 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 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: Color image signals, as derived, e.g., by interpolating the output from a color filter array are arranged in pixels, each pixel having associated detected color information for a first color as well as undetected filled-in color information for at least a second and a third color. The images are thus exposed to false color and zipper effect artifacts, and are subject to processing preferably including the steps of: checking the images for the presence of zipper effect artifacts, and i) if said checking reveals the presence of zipper effect artifacts, applying a zipper effect removal process to said image signals; ii) if said checking fails to reveal the presence of zipper effect artifacts, applying a false color removal process to said image signals. False color and zipper effect artifacts are thus preferably both reduced by adaptively using the zipper effect removal process and the false color removal process.