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 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 filtering the noise of a sequence of digital images in CFA format comprising the following phases:

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.

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 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 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.