Abstract:
A digital image color correction device employing fuzzy logic, for correcting a facial tone image portion of a digital video image, characterized in that it comprises: a pixel fuzzifier unit (1) receiving in input a stream of pixels belonging to a sequence of correlated frames of a digital video image and computing a multi level value representing a membership of each pixel to a skin color class; a global parameter estimator (2) receiving in input each of said pixel and the relative membership value, and computing a first and a second parameter which define the characteristics of a portion of said image that belongs to said skin color class; a processing unit (3) connected downstream to said global parameter estimator and to said pixel fuzzifier unit and adapted to correct each of the pixels of said portion of the image that belongs to said skin color class, according to said first global parameter (300), to obtain corrected pixels; and a processing switch (4) for outputting said pixels or said corrected pixels according to said second global parameter (400).
Abstract:
A method of filtering and an image filter (10) is disclosed. The filter is provided for a digital camera including image sensors sensitive to light, a color filter placed over sensitive elements of the sensors and patterned according to a Bayer mosaic pattern layout and an interpolation algorithm joining together the digital information provided by differently colored adjacent pixels in said Bayer pattern. The filter (10) is adaptive and includes a noise level computation block (26) for operating directly on a said Bayer pattern data set of for each color channel thus removing noise while simultaneously preserving picture detail.
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 mean 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. A variant of the method can also be applied directly to digital images in CFA (Colour Filter Array) format.
Abstract:
A method (300) of compressing a digital image including a matrix of elements each one consisting of at least one component of different type representing a pixel, the method comprising the steps of splitting (340) the digital image into a plurality of blocks and calculating, for each block, a group of DCT coefficients for the components of each type, and quantizing (350a-355a) the DCT coefficients of each group using a corresponding quantization table scaled by a gain factor for achieving a target compression factor; the method also comprises the steps of further quantizing (350-355) the DCT coefficients of each group using the corresponding quantization table scaled by a pre-set factor, arranging (360) the further quantized DCT coefficients in a zig-zig vector, calculating (365-370) a basic compression factor provided by the quantization table scaled by the pre-set factor as a first function of the zigzag vector, and estimating (375) the gain factor as a second function of the basic compression factor, the second function being determined experimentally according to the target compression factor.