Abstract: A system and method of reducing noise in output image data is provided. Grayscale image data having a plurality of pixels is received and processed. During processing, pixels which may produce noise are identified, and a mask associated with the image data is generated. The mask provides information related to the pixels, such as opaque and transparent regions for overlaying the pixels. The image data and the mask are compressed and stored. The mask assists in preventing the identified pixels from being visible when the image data is output, thereby reducing the noise in the image.

Abstract: One embodiment is a method for suppressing background inaccuracies in binary to grayscale image conversion. A binary image is converted to a grayscale image using a neighbor map. An image enhancement function is applied to the grayscale image to suppress background inaccuracies in the grayscale image. Another embodiment is method for converting a binary pixel of a binary image to a grayscale pixel of a grayscale image and suppressing noise in the grayscale image using selective filtering of the binary image. Another embodiment is a method for converting a binary image to a first grayscale image and suppressing noise in the first grayscale image to produce a noise suppressed grayscale image using selective filtering of the first grayscale image.

Abstract: A method and system reconstructs a contone image from a binary image by first tagging pixels to identify one of a multiplicity of image content types. The tag information and the pattern of bits surrounding the pixel to be converted to a contone value are used to reconstruct a contone image from a binary image. The pattern of bits in the neighborhood is used to generate a unique identifier. The unique identifier is used as the address for a lookup table with the contone value to be used wherein each lookup table corresponds to an image context type.

Abstract: A light compression method that error diffuses image data provided with luminance and chrominance channels. During error diffusion, a higher number of bits are allocated to the luminance channel. A decompression method for the image data based on sigma filtering is also provided. By manipulating the bits in the luminance and chrominance color spaces, the image output quality may be increased in reconstructed images.

Abstract: One embodiment is a method for suppressing background inaccuracies in binary to grayscale image conversion. A binary image is converted to a grayscale image using a neighbor map. An image enhancement function is applied to the grayscale image to suppress background inaccuracies in the grayscale image. Another embodiment is method for converting a binary pixel of a binary image to a grayscale pixel of a grayscale image and suppressing noise in the grayscale image using selective filtering of the binary image. Another embodiment is a method for converting a binary image to a first grayscale image and suppressing noise in the first grayscale image to produce a noise suppressed grayscale image using selective filtering of the first grayscale image.

Abstract: A method and system reconstructs a contone image from a binary image by first tagging pixels to identify one of a multiplicity of image content types. The tag information and the pattern of bits surrounding the pixel to be converted to a contone value are used to reconstruct a contone image from a binary image. The pattern of bits in the neighborhood is used to generate a unique identifier. The unique identifier is used as the address for a lookup table with the contone value to be used. A filter also generates a contone value. A selector selects between the look-up table contone value and the filter contone value based an image context type.

Abstract: A method and system reconstructs a contone image from a binary image by first tagging pixels to identify one of a multiplicity of image content types. The tag information and the pattern of bits surrounding the pixel to be converted to a contone value are used to reconstruct a contone image from a binary image. The pattern of bits in the neighborhood is used to generate a unique identifier. The unique identifier is used as the address for a lookup table with the contone value to be used wherein each lookup table corresponds to an image context type.

Abstract: A method and system reconstructs a contone image from a binary image by first tagging pixels to identify one of a multiplicity of image content types. The tag information and the pattern of bits surrounding the pixel to be converted to a contone value are used to reconstruct a contone image from a binary image. The pattern of bits in the neighborhood is used to generate a unique identifier. The unique identifier is used as the address for a lookup table with the contone value to be used wherein each lookup table corresponds to an image context type.

Abstract: A system and method of reducing noise in output image data is provided. Grayscale image data having a plurality of pixels is received and processed. During processing, pixels which may produce noise are identified, and a mask associated with the image data is generated. The mask provides information related to the pixels, such as opaque and transparent regions for overlaying the pixels. The image data and the mask are compressed and stored. The mask assists in preventing the identified pixels from being visible when the image data is output, thereby reducing the noise in the image.

Abstract: A light compression method that error diffuses image data provided with luminance and chrominance channels. During error diffusion, a higher number of bits are allocated to the luminance channel. A decompression method for the image data based on sigma filtering is also provided. By manipulating the bits in the luminance and chrominance color spaces, the image output quality may be increased in reconstructed images.

Abstract: One embodiment is a method for suppressing background inaccuracies in binary to grayscale image conversion. A binary image is converted to a grayscale image using a neighbor map. An image enhancement function is applied to the grayscale image to supress background inaccuracies in the grayscale image. Another embodiment is method for converting a binary pixel of a binary image to a grayscale pixel of a grayscale image and suppressing noise in the grayscale image using selective filtering of the binary image. Another embodiment is a method for converting a binary image to a first grayscale image and suppressing noise in the first grayscale image to produce a noise suppressed grayscale image using selective filtering of the grayscale image.