Abstract: Provided in an example is a method of compressing a digital image includes dividing the image into cells of constant physical size regardless of resolution of the image to produce cell data for each cell which defines content of the cell and compressing the cell data.

Abstract: A method for compressing a digital image to be printed, the image consisting of pixels. It is determined, for blocks of pixels, whether a block contains a graphical structure that is to be maintained without loss because it is of a type that can be accurately perceived by a human observer. The block is encoded losslessly into a less voluminous format, if such a graphical structure has been found. Otherwise, the block is compressed lossily, if no such graphical structure has been found.

Abstract: Provided in an example is a method of compressing a digital image includes dividing the image into cells of constant physical size regardless of resolution of the image to produce cell data for each cell which defines content of the cell and compressing the cell data.

Abstract: A method of compressing a digital image comprises dividing 12 the image into cells of constant physical size regardless of resolution of the image to produce cell data for each cell which defines content of the cell and compressing 14 the cell data.

Abstract: Method and system embodiments of the present invention are directed to automated identification of regions within digitally-encoded images that correspond to objects and features of scenes captured in the digitally-encoded images, a process referred to as ‘perceptual segmentation’ of an image. Regions or segments within an image are first identified by any of various region-identifying or segmentation methods. For each region or segment, features of pixels within the region or segment are employed to compute one or more segment features. The segment features are used, in turn, to identify the region or segment as belonging to a particular type of region or segment, and the region is then accordingly labeled or tagged as a region or segment of the determined type.

Abstract: Method and system embodiments of the present invention are directed to automated identification of regions within digitally-encoded images that correspond to objects and features of scenes captured in the digitally-encoded images, a process referred to as ‘perceptual segmentation’ of an image. Regions or segments within an image are first identified by any of various region-identifying or segmentation methods. For each region or segment, features of pixels within the region or segment are employed to compute one or more segment features. The segment features are used, in turn, to identify the region or segment as belonging to a particular type of region or segment, and the region is then accordingly labeled or tagged as a region or segment of the determined type.

Abstract: Systems and methods of face and skin sensitive image enhancement are disclosed. In one aspect, a face map that includes for each pixel of an input image a respective face probability value indicating a degree to which the pixel corresponds to a human face is calculated. A skin map that includes for each pixel of the input image a respective skin probability value indicating a degree to which the pixel corresponds to human skin is ascertained. The input image is enhanced with an enhancement level that varies pixel-by-pixel in accordance with the respective face probability values and the respective skin probability values. In another aspect, a facial content measurement value indicating a degree to which an input image contains human face content is ascertained. A tone-correction process is tuned in accordance with the facial content measurement value. The input image is enhanced in accordance with the tuned tone-correction process.

Abstract: In a method of processing an image containing undesirable pixels, a coarse identification of a location of the undesirable pixels is received. The coarse identification includes identification of at least one undesirable pixel and at least one desirable pixel in the image. An area in the image to be analyzed for undesirable pixel values is automatically determined according to the coarse identification received. In addition, in the area determined to be analyzed, the pixels are automatically classified as one of undesirable and desirable and the classifications of the pixels are stored.

Abstract: In a method of automatically replacing undesirable pixels in an image, a local neighborhood of pixels is identified around an undesirable pixel. In addition, secondary neighborhoods of pixels are identified and feature values of the pixels contained in the local neighborhood and each of the secondary neighborhoods are calculated. The secondary neighborhoods having feature values within a predetermined range of the local neighborhood feature value are classified as candidates for pixel value replacement. Moreover, a replacement pixel value from at least one of the secondary neighborhoods classified as a candidate for pixel value replacement is determined and the undesirable pixel value is replaced with the replacement pixel value.

Abstract: A method for compressing a digital image to be printed, the image consisting of pixels. It is determined, for blocks of pixels, whether a block contains a graphical structure that is to be maintained without loss because it is of a type that can be accurately perceived by a human observer. The block is encoded losslessly into a less voluminous format, if such a graphical structure has been found. Otherwise, the block is compressed lossily, if no such graphical structure has been found.

Abstract: Imaging systems, articles of manufacture, and imaging methods are described according to aspects of the disclosure. According to one embodiment, an imaging system includes processing circuitry configured to access image data of a plurality of pixels of an image, to provide a plurality of representations of the image data, to determine contrast difference between the representations of the image data for a respective one of the pixels, to identify the one of the pixels as being defective using the determined contrast difference, and to provide replacement image data for the one of the pixels identified as defective and which is different than the accessed image data for the one of the pixels identified as defective.

Abstract: In one aspect, an image is quantized by assigning sub-ranges of pixel values in the image to respective quantization levels. The quantized image is encoded based at least in part on a mask lookup table assigning index values to respective masks, wherein each mask corresponds to a respective spatial distribution of the quantization levels. In another aspect, a code corresponding to an encoded image with pixel values quantized to respective quantization levels is received. The code is decoded based at least in part on a mask lookup table assigning index values to respective masks, wherein each mask corresponds to a respective spatial distribution of the quantization levels.

Abstract: Systems, methods, and software to automatically detect print defects in printed matter. Some embodiments include receiving a reference image and a scanned image, wherein the reference image and the scanned image are of the same subject matter and generating a plurality of detail maps of the reference image and the scanned image at each one or more resolutions to derive one or more detail maps of each image at each resolution. The detail maps, in some embodiments, are generated by identifying differences between pixels in each of one or more directions. The embodiments further include dividing the detail maps of each image into blocks of equal image proportion and calculate an activity measure of each block in each of the detail maps. These embodiments further calculate similarity measures between the blocks of reference image detail maps and the respective blocks of the scanned image detail maps.

Abstract: A method of compressing a digital image comprises dividing 12 the image into cells of constant physical size regardless of resolution of the image to produce cell data for each cell which defines content of the cell and compressing 14 the cell data.

Abstract: Systems and methods of face and skin sensitive image enhancement are disclosed. In one aspect, a face map that includes for each pixel of an input image a respective face probability value indicating a degree to which the pixel corresponds to a human face is calculated. A skin map that includes for each pixel of the input image a respective skin probability value indicating a degree to which the pixel corresponds to human skin is ascertained. The input image is enhanced with an enhancement level that varies pixel-by-pixel in accordance with the respective face probability values and the respective skin probability values. In another aspect, a facial content measurement value indicating a degree to which an input image contains human face content is ascertained. A tone-correction process is tuned in accordance with the facial content measurement value. The input image is enhanced in accordance with the tuned tone-correction process.

Abstract: Provided are codes that may be applied to a sheet of paper or other surface, as well as techniques for decoding such codes. Using such codes and decoding techniques permits identification of the position of a pen (e.g., a digital pen) on the paper or other surface, by observing only a small field of the surface. Moreover, the position often can be identified even in the presence of arbitrary rotation and certain errors (e.g., due to dust or stray markings on the paper).

Abstract: Provided are codes that may be applied to a sheet of paper or other surface, as well as techniques for decoding such codes. Using such codes and decoding techniques permits identification of the position of a pen (e.g., a digital pen) on the paper or other surface, by observing only a small field of the surface. Moreover, the position often can be identified even in the presence of arbitrary rotation and certain errors (e.g., due to dust or stray markings on the paper).

Abstract: Imaging systems, articles of manufacture, and imaging methods are described according to aspects of the disclosure. According to one embodiment, an imaging system includes processing circuitry configured to access image data of a plurality of pixels of an image, to provide a plurality of representations of the image data, to determine contrast difference between the representations of the image data for a respective one of the pixels, to identify the one of the pixels as being defective using the determined contrast difference, and to provide replacement image data for the one of the pixels identified as defective and which is different than the accessed image data for the one of the pixels identified as defective.

Abstract: Systems, methods, and software to automatically detect print defects in printed matter. Some embodiments include receiving a reference image and a scanned image, wherein the reference image and the scanned image are of the same subject matter and generating a plurality of detail maps of the reference image and the scanned image at each one or more resolutions to derive one or more detail maps of each image at each resolution. The detail maps, in some embodiments, are generated by identifying differences between pixels in each of one or more directions. The embodiments further include dividing the detail maps of each image into blocks of equal image proportion and calculate an activity measure of each block in each of the detail maps. These embodiments further calculate similarity measures between the blocks of reference image detail maps and the respective blocks of the scanned image detail maps.

Abstract: In one aspect, an image is quantized by assigning sub-ranges of pixel values in the image to respective quantization levels. The quantized image is encoded based at least in part on a mask lookup table assigning index values to respective masks, wherein each mask corresponds to a respective spatial distribution of the quantization levels. In another aspect, a code corresponding to an encoded image with pixel values quantized to respective quantization levels is received. The code is decoded based at least in part on a mask lookup table assigning index values to respective masks, wherein each mask corresponds to a respective spatial distribution of the quantization levels.