Abstract: A method for estimating the white Gaussian noise level that corrupts a digital image by discriminating homogeneous blocks from blocks containing a textured area and skipping these last blocks when evaluating the noise standard deviation.

Abstract: According to the novel method, roto-translational and zooming parameters describing spurious motion effects are determined by exploiting any of the many block matching algorithms commonly used for motion estimation for calculating a motion vector for all or for a selected number of blocks of pixels of the current frame that is processed. Some of the so calculated motion vectors are not taken into account for estimating spurious motion effects. The roto-translational and zooming parameters describing what is considered to be spurious global motion between a current frame and the precedent frame of the sequence, are calculated by processing the selected motion vectors of blocks of pixels of the frame through a recursive procedure that includes computing error values and readjusting the roto-translational and zooming parameters based on the error values.

Abstract: A digital image processing system and method for removing motion effects from images of a video sequence, and generating corresponding motion compensated images.

Abstract: A method of processing digital images to reduce the effects of color bleeding. Chrominance components for pixels in a working window are determined and weights are assigned to the pixels in the working window. A chrominance correction for a center pixel in the working window is generated based on the chrominance components and the assigned weights. Fuzzy variables and thresholds may be applied to generate the assigned weights and the chrominance correction.

Abstract: The system carries out conversion of digital video signals organized in blocks of pixels from a first format to a second format. The second format is a format compressed via vector quantization. The vector quantization is performed by means of repeated application of a scalar quantizer to the pixels of said blocks with a quantization step (Q) determined in an adaptive way according to the characteristics of sharpness and/or brightness of the pixels and representing said vector quantization in a n-dimensional space indicative of the characteristics on n of said pixels in the block partitioned into cells of size proportional to said quantization step, each cell being assigned to an appropriate binary code, wherein said process further includes identifying at least one symmetry element in said n-dimensional space suitable for separating at least two symmetrical set of cells, and selecting one of said at least two symmetrical set of cells for the assignment of said binary codes.

Abstract: The method for block coding data, such as video data, via a compression operation includes applying to input-data blocks a discrete-cosine-transform (DCT) operation and a quantization operation to produce compressed-data blocks. The compressed-data blocks are subjected to a coding operation to obtain compressed output flows; and an inverse-quantization operation and an inverse-discrete-cosine-transform (IDCT) operation are applied on the compressed-data blocks to obtain reconstructed blocks. The method includes controlling generation of mismatch errors from the input-data blocks by detecting data blocks from the input-data blocks and compressed-data blocks that are liable to cause mismatch errors, and modifying the blocks that are liable to cause mismatch errors prior to the coding operation.

Abstract: A method for correcting an image from defects and filtering from Gaussian noise corrects each pixel of the image when it is considered defective and filters it from Gaussian noise in one-pass. The one-pass improves the speed for performing the correcting and filtering. The drawbacks associated with choosing incompatible defect correction and filtering operations are overcome.

Abstract: A digital image processing system and method for removing motion effects from images of a video sequence, and generating corresponding motion compensated images.

Abstract: A method of processing and device configure to process digital images to enhance image quality and correct motion blur. A number N of images of a scene are captured with an exposure time T. An order of sharpness of the images is determined and the sharpest image is used as a reference image for generating an output image.

Abstract: According to the novel method, roto-translational and zooming parameters describing spurious motion effects are determined by exploiting any of the many block matching algorithms commonly used for motion estimation for calculating a motion vector for all or for a selected number of blocks of pixels of the current frame that is processed. Some of the so calculated motion vectors are not taken into account for estimating spurious motion effects. The roto-translational and zooming parameters describing what is considered to be spurious global motion between a current frame and the precedent frame of the sequence, are calculated by processing the selected motion vectors of blocks of pixels of the frame through a recursive procedure that includes computing error values and readjusting the roto-translational and zooming parameters based on the error values.

Abstract: For each color channel, the process includes gathering Bayer pattern pixel values by pairs, each pair being composed by two successive pixels belonging to the channel along the scanning direction of the pixels of the image, thus each pair of values representing a current input vector, and calculating a predictor vector of the input vector in terms of the differences between the values defining the input vector and a pair of prediction values generated according to a certain criterion, for representing a prediction error. The process further includes quantizing each so calculated predictor vector according to a heavier or lighter degree of quantization depending on whether the predictor vector is representative of an area of relatively uniform color of the image or of an area of relatively abrupt changes of colors of the image, and generating a multibit code representative of the quantized predictor vector of the input vector according to a certain compression ratio.

Abstract: A method for correcting an image from defects and filtering from Gaussian noise corrects each pixel of the image when it is considered defective and filters it from Gaussian noise in one-pass. The one-pass improves the speed for performing the correcting and filtering. The drawbacks associated with choosing incompatible defect correction and filtering operations are overcome.

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 correcting an image from defects and filtering from Gaussian noise corrects each pixel of the image when it is considered defective and filters it from Gaussian noise in one-pass. The one-pass improves the speed for performing the correcting and filtering. The drawbacks associated with choosing incompatible defect correction and filtering operations are overcome.

Abstract: A method for image compression of a set of image data includes performing a quantization operation on the image data. The quantization operation may include controlling a compression factor by applying a scaled quantization level obtained by multiplying a first quantization level by a gain factor. The gain factor may be updated as a function of a bit per pixel value of a compressed image. The update operation may include an iterative procedure including at least one iteration step that provides for updating a current gain factor as a function of a previous gain used for performing a previous compression step and as a function of a ratio of the bit per pixel value of the compressed image at the previous compression step to a target bit per pixel value. The method may be used in Joint Photographic Experts Group (JPEG) image processing and digital still cameras.

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 processing digital images to reduce the effects of color bleeding. Chrominance components for pixels in a working window are determined and weights are assigned to the pixels in the working window. A chrominance correction for a center pixel in the working window is generated based on the chrominance components and the assigned weights. Fuzzy variables and thresholds may be applied to generate the assigned weights and the chrominance correction.

Abstract: A method of processing digital images by transforming a set of pixels from a three-dimensional space to a normalized two-dimensional space, determining a membership class and membership class level of each pixel in the set of pixels, and selectively modifying colors of pixels in the set of pixels based on the determined membership classes and membership class levels.

Abstract: A method for estimating the white Gaussian noise level that corrupts a digital image by discriminating homogeneous blocks from blocks containing a textured area and skipping these last blocks when evaluating the noise standard deviation.

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.