Abstract: Processing of a pixel of a digital image includes mapping intensity of the pixel as a smooth, non-linear continuous function of the intensity and minimum and maximum intensities of a local pixel neighborhood of the pixel.

Abstract: A group of pixels of a digital image is processed to reduce bleed-through. The processing includes generating an upper bound for each pixel of the group; and taking a weighted average of the upper bound and original pixel intensity for each pixel of the group.

Abstract: Chromatic bleeding artifacts in a digital image are reduced by modifying chrominance values of at least some pixels in the digital image. The chrominance values are modified according to luminance values and chromatic dynamic range.

Abstract: Processing of a pixel of a digital image includes sharpening a digital image, while boldening dark features in the digital image as a non-decreasing function of local contrast.

Abstract: Processing of a pixel in a digital image includes performing inverse halftoning on the pixel with respect to a local pixel neighborhood; and performing selective sharpening on the inverse halftoned pixel with respect to the local pixel neighborhood.

Abstract: Boundary curves of a source image are identified. Each pixel of a distance map is associated with a corresponding region of the source image. Each pixel is assigned a calculated distance value corresponding to the Euclidean distance between a center of that pixel and the nearest point of the closest boundary curve. The nearest point is located to sub-pixel accuracy. A method of compressing and decompressing a source image includes the step of generating a first distance map having a first resolution. The first distance map is downsampled to generate a second distance map having a second resolution. The second distance map may be interpolated to generate an interpolated distance map having the first resolution. A soft threshold is applied to the interpolated distance map to generate a reconstructed source image having the first resolution.

Abstract: A system and method of removing background noise from a digital image of a scanned document is described. The system and method is a reversible background noise removal technique that allows a user to select whether background noise is removed or not. In addition, since the present invention divides the background noise removal operations into a two phase process, the overall efficiency of the system and method are significantly improved.

Abstract: A method of deriving from an existing selective image smoothing filter either a corresponding filter for selective image sharpening, or a corresponding filter for both selective image smoothing and selective image sharpening. The selective sharpening filter can be implemented quickly by using implementations of the existing selective smoothing filter and a derived matching non-selective smoothing filter as black boxes and combining their outputs in a simple manner. Alternatively, the derived selective sharpening filter can be implemented by inlining the combination of the implementations of the existing selective smoothing.

Abstract: Image sharpening is performed by applying variable contrast stretching to pixels of interest in a digital image. For each pixel of interest, the amount of contrast stretching is a function of minimum and maximum intensity values in a local pixel neighborhood.

Abstract: Processing of a pixel in a digital image includes performing inverse halftoning on the pixel with respect to a local pixel neighborhood; and performing selective sharpening on the inverse halftoned pixel with respect to the local pixel neighborhood.

Abstract: Processing of a pixel of a digital image includes sharpening a digital image, while boldening dark features in the digital image as a non-decreasing function of local contrast.

Abstract: Blind inverse halftoning on a digital image is performed by applying a robust convolution filter to the digital image.

Abstract: A system and method of gamut mapping/clipping is described. The system and method applies to original image data color values in an original color space that have been transformed to obtain an original luminance value having an associated luminance/chrominance based color space and original chrominance values. The original luminance value is processed to obtain a processed color value having a processed luminance value and the original chrominance values. According to the system and method, the processed color value is mapped back into the original color gamut by selecting a target color value on a luminance axis. A different target color value is selectable for each of a plurality of color values of the image data. A mapped color value is then determined by linearly projecting from the processed color value towards the target color value. The mapped color value is located at the intersection of the gamut boundary of the original color space and the projection.

Abstract: A group of pixels of a digital image is processed to reduce bleed-through. The processing includes generating an upper bound for each pixel of the group; and taking a weighted average of the upper bound and original pixel intensity for each pixel of the group.

Abstract: Processing of a pixel of a digital image includes mapping intensity of the pixel as a smooth, non-linear continuous function of the intensity and minimum and maximum intensities of a local pixel neighborhood of the pixel.

Abstract: A system and method of image processing for smoothing, denoising, despeckling and sharpening scanned document images which is performed prior to a compression. The scanned image is selectively smoothed by anisotropic diffusion filtering in a single iteration with a 3×3 kernel, which provides denoising, edge-preserving smoothing. The smoothed image data is then selectively sharpened using variable contrast mapping that provides overshoot-free variable-sharpening and despeckling. Image quality is improvides while increasing compressibility of the image.

Abstract: A method of deriving from an existing selective image smoothing filter either a corresponding filter for selective image sharpening, or a corresponding filter for both selective image smoothing and selective image sharpening. The selective sharpening filter can be implemented quickly by using implementations of the existing selective smoothing filter and a derived matching non-selective smoothing filter as black boxes and combining their outputs in a simple manner. Alternatively, the derived selective sharpening filter can be implemented by inlining the combination of the implementations of the existing selective smoothing.

Abstract: A method of deriving from an existing selective image smoothing filter either a corresponding filter for selective image sharpening, or a corresponding filter for both selective smoothing and selective image sharpening. The selective sharpening filter can be implemented quickly by using implementations of the existing selective smoothing filter and a derived matching non-selective smoothing filter as black boxes and combining their outputs in a simple manner. Alternatively, the derived selective sharpening filter can be implemented by inlining the combination of the implementations of the existing selective smoothing.

Abstract: Compression of a digital image is performed by bit-depth truncating a luminance channel of the digital image and performing lossless compression on the bit-depth truncated luminance channel; and performing lossy compression on chrominance channels of the digital image.

Abstract: A sensor image is processed by applying a first demosaicing kernel to produce a sharp image; applying a second demosaicing kernel to produce a smooth image; and using the sharp and smooth images to produce an output image.