Abstract:
An adaptive filtering method and apparatus for descreening a scanned halftoned image representation is disclosed. The apparatus includes an image input subsystem; a processing subsystem for processing halftoned image data provided by the image input subsystem; and software/firmware means operative on the processing subsystem for a) low-pass filtering a halftoned input pixel value provided by the image input subsystem to produce a low-pass filtered pixel value; b) notch-filtering the halftoned input pixel value to produce a notch-filtered pixel value; c) determining a local contrast value for the halftoned input pixel value; and d) producing a descreened output pixel value based on the low-pass filtered pixel value, the notch-filtered pixel value, or a combination of the low-pass filtered pixel value and the notch-filtered pixel value depending on the local contrast value.
Abstract:
A method and system for image processing, in conjunction with classification of images between natural pictures and synthetic graphics, using SGLD texture (e.g., variance, bias, skewness, and fitness), color discreteness (e.g., R_L, R_U, and R_V normalized histograms), or edge features (e.g., pixels per detected edge, horizontal edges, and vertical edges) is provided. In another embodiment, a picture/graphics classifier using combinations of SGLD texture, color discreteness, and edge features is provided. In still another embodiment, a nullsoftnull image classifier using combinations of two (2) or more SGLD texture, color discreteness, and edge features is provided. The nullsoftnull classifier uses image features to classify areas of an input image in picture, graphics, or fuzzy classes.
Abstract:
This invention relates to a method and apparatus for segmenting an image using a combination of image segmentation techniques. More particularly, the invention is directed to an improved image segmentation technique for use in an image processing system that performs at least two distinct image segmentation processes on an image and combines the results to obtain a combined multi-layer representation of the image that can be suitably processed. In a specific example, a block based segmentation technique is performed on an image to generate a MRC (mixed raster content) representationnullhaving foreground, background and selector layers. A pixel based segmentation technique is also performed on the image to generate rendering hints. The MRC representation and the rendering hints are then combined to obtain a four (4) layer representation of the image. The four layer representation is subsequently processed as required by the image processing system, e.g. compressed and stored.
Abstract:
A method and system for image processing, in conjunction with classification of images between natural pictures and synthetic graphics, using SGLD texture (e.g., variance, bias, skewness, and fitness), color discreteness (e.g., R_L, R_U, and R_V normalized histograms), or edge features (e.g., pixels per detected edge, horizontal edges, and vertical edges) is provided. In another embodiment, a picture/graphics classifier using combinations of SGLD texture, color discreteness, and edge features is provided. In still another embodiment, a nullsoftnull image classifier using combinations of two (2) or more SGLD texture, color discreteness, and edge features is provided. The nullsoftnull classifier uses image features to classify areas of an input image in picture, graphics, or fuzzy classes.
Abstract:
A method for neutral pixel detection using color space feature vectors wherein one color space coordinate represents lightness is provided. The method includes the following steps: a) receiving an input image represented in a first color space; b) converting the input image to a second color space wherein one coordinate represents lightness; c) selecting a pixel in the second color space representation to be classified; d) computing second color space feature vectors associated with the selected pixel; and e) classifying the selected pixel between neutral and color classes based on the values computed for the second color space feature vectors. Typically, the input image is processed using a smoothing filter to create a smoothed input image prior to the conversion to the second color space. The method can be adapted to page processing or strip processing schemes with respect to the input image.
Abstract:
A method for processing digital images to be displayed, stored, or printed, to eliminate blooming and other artifacts. The system utilizes morphological processes to isolate and modify image structures susceptible to marking process artifacts and then combines the modified image structures with the input image to produce a printable image that may be rendered on a given printer.