Abstract: Several quality-aware transcoding systems and methods are described, in which the impact of both quality factor (QF) and scaling parameter choices on the quality of transcoded images are considered in combination. A basic transcoding system is enhanced by the addition of a quality prediction look-up table, and a method of generating such a table is also shown.

Abstract: A method performed by a software process executing on a computer system, includes obtaining a digital image having a plurality of pixels encoded in a YUV color space. Each pixel has a luma component of value Y, a blue color-difference component of value U and a red color-difference component of value V. For a specified pixel, the method includes calculating whether U is less than a first threshold and V is greater than a second threshold. The method further includes determining whether the specified pixel potentially depicts an orange hue depending on a result of the calculation.

Abstract: Method, computer program product, and apparatus are provided for identifying a graphic symbol within an image obtained by optical scanning. An image intensity is measured for each of a plurality of columns of the image, wherein each column has a length that extends across the graphic symbol in a first direction, and wherein the plurality of columns collectively extend across the graphic symbol in a second direction. The graphic symbol is then identified by matching a profile of the image intensity to a predetermined image intensity profile associated with a given graphic symbol. Optionally, the image is a digital image and the image intensity for each column is the sum of the image intensity for each pixel in that individual column. An image intensity differential between adjacent columns may be calculated for matching with a predetermined differential profile or comparison with an electronic profile generated by a magnetic scan.

Abstract: A method performed by a software process executing on a computer system, includes accessing a digital image having a plurality of pixels encoded in a color space that defines hue as a pair of Cartesian coordinates. The method also includes calculating a chroma value for a specified pixel by determining a distance between a point corresponding to a hue coordinate pair value for the specified pixel and a Cartesian origin point. The calculated chroma value is compared to a predetermined threshold and an image processing operation is performed on the digital image based on a result of the comparison.

Abstract: A method, performed by a software process executing on a computer system, includes accessing a digital image comprising a plurality of pixels. The method also includes determining whether one or more pixels bounding a first rectangular sub-region of a predetermined size within the digital image satisfy a specified criterion. If a predetermined percentage of bounding pixels satisfy the specified criterion, the method assumes that all pixels within the first rectangular sub-region also satisfy the specified criterion. The method further includes selectively executing an image analysis algorithm on the digital image using the assumption that all pixels within the rectangular sub-region also satisfy the specified criterion.

Abstract: An image editing apparatus includes an image input unit including an image pickup circuit which takes a picture of a subject to obtain an image of a subject. A face detection circuit detects an image of a face of the subject from the image obtained from the image input unit. A face expression detection circuit detects at least any one of direction and expression of the face of the subject, based on the image of the face detected by the face detection circuit. A pupil detection circuit detects images of pupils of the subject, based on the image of the face detected by the face detection circuit. A catch-light composition circuit composes different catch-lights on the images of the pupils detected by the pupil detection circuit, according to any one of the direction and expression of the face detected by the face expression detection circuit.

Abstract: A system and method for predicting a file size of an image subject to transformation by scaling and a change about at least one quality-controlling parameter, in which an input receives (a) the file size of the image before transformation, (b) information about at least one quality-controlling parameter of the image before transformation, (c) information about at least one quality-controlling parameter for application to the image during transformation, and (d) a scaling factor for application to the image during transformation. A relative size prediction is calculated on the basis of the received quality-controlling parameters information and scaling factor. The file size of the image after transformation is finally calculated as a function of the file size of the image before transformation and the calculated relative size prediction.

Abstract: Techniques are provided to analyze video frames of a video signal in order to distinguish regions containing a face (and body torso) from regions that contain a relatively static background. The region containing the face is referred to as a foreground region. A current video frame is divided into a plurality of elements and the foreground regions and background regions are detected. The background regions of a subsequent video frame are detected/registered using the foreground regions of the current video frame. The foreground regions of the subsequent video frame are determined using the background regions of the current video frame as a temporal reference.

Abstract: A digital media with encoded audio-visual content includes an encoded token. The token comprises visual data having defined characteristics, which are designed such that when the audio-visual content is output as analog output and then re-recorded as digital data, the resulting digital data includes an altered token. Digital data may be processed to detect altered tokens indicating that the data was recorded from an analog output. When an altered token is detected, the copy may be considered to be an unauthorized copy and handled accordingly.

Abstract: A method and system of restoring an image using a frequency-based image model is provided. A method of restoring an image using a frequency-based image model, the method including: transforming an original image into a frequency domain and generating a transformation image; copying the transformation image in any one domain of domains in which the original image is extended and which are divided into blocks; and inferring a high frequency component of block domains, and restoring the block using the transformation image copied in the any one domain.

Abstract: A clustering unit calculates, for clusters in a descending order of the number of pixels belonging thereto, a distance from a feature vector of a processing object pixel and a representative feature vector of an object cluster, and compares the distance with a first threshold. The processing object pixel is stored in a memory or the like as a pixel belonging to an object cluster when the distance is determined to be less than or equal to the first threshold.

Abstract: An image processing apparatus includes an input unit receiving an encoded image data stream; a decoding processor decoding the stream to obtain image data; a first storage storing the image data; a second storage storing the image data and having a storage area storing at least one picture whose size is the largest of image data to be decoded; a controller analyzing the stream and storing the image data in the first and second storages according to an analysis result; and an output unit reading and outputting the stored pictures in a display order. The controller sets storage areas in the first storage according to image size information, stores the image data in the storage areas, determines whether the image size changes according to the analysis result, and, when the image size changes, stores image data of a picture displayed immediately before the image size changes in the second storage.

Abstract: The present invention relates to a method of and apparatus for image analysis and in particular may relate to the detection of cross-fades in film or video sequences. The invention relates in particular to a method of analysing an image of a sequence of images to determine a cross-fade measure based on determined temporal picture information transitions associated with picture elements of the image. In particular, the cross-fade measure may be determined based on the extent to which the temporal picture information transitions are uniform. The method and apparatus of the invention can provide a measure of likelihood of a cross-fade in a single pass. In addition the described method can be accomplished in real-time or close to real-time. In addition the cross-fade detection results are comparable with, or better than, the results achieved by the prior art methods.

Abstract: A method of detecting and compensating fail pixels in a holographic storage system. The method includes steps of: providing a plurality of image frames to show on a data plane for all pixels on the data plane being capable of outputting a light state or a dark state; sequentially recording the image frames into a storage medium; detecting the image frames by using a detecting apparatus for all pixels on the detecting apparatus being capable of outputting sensing signals corresponding to the light state and the dark state; defining a sensing difference value, which is a difference of the sensing signal outputting the light state and the dark state generated by one pixel; comparing the sensing difference value with a threshold value; and defining the corresponding pixel is a fail pixel if the sensing difference value is smaller than the threshold value.

Abstract: An image processing method that demosaicks a mosaic input image to generate a full color output image. The image processing method calculates both vertical and horizontal luminance-chrominance difference components for each pixel of the mosaic input image. Next, the image processing method calculates an enhanced version of both vertical and horizontal luminance-chrominance difference components for each pixel of the mosaic input image. Then, the image processing method interpolates a G component for each of the original R and B components. Next, the image processing method detects a signal overshoot or undershoot in each interpolated G component and to clamps each interpolated G component with a detected signal overshoot or undershoot to the closest neighboring original G component. Next, the image processing method interpolates missing R and/or B components in each pixel location of the captured image.

Abstract: Systems and methods are provided for reducing data size of at least one bitmap image, wherein the bitmap image comprises a plurality of color blocks, wherein each color block is associated with a distinct color plane. In some embodiments, the bitmap image may be compressed. At least one compressed color block that is contained in a transfer frame may be determined, based on information pertaining to a physical offset between successive color planes when they are rendered on a print medium. Further, at least one compressed color block in the transfer frame may be tagged, if the size of the transfer frame exceeds a threshold, and the resolution of the at least one compressed color block that is tagged may be reduced.

Abstract: Provided is an apparatus and method for transforming between a DCT coefficient and a DWT coefficient. The transforming apparatus includes a first fundamental matrix calculating unit, a second fundamental matrix calculating unit, and a DWT coefficient calculating unit. The first fundamental matrix calculating unit calculates a first fundamental matrix by multiplying an N×N forward DWT transform matrix and an N×N matrix that has diagonal components corresponding to a transpose matrix of an 8×8 DCT transform matrix and the remaining components corresponding to an 8×8 matrix with all elements being zero. The second fundamental matrix calculating unit calculates a second fundamental matrix by multiplying an M×M matrix, which has diagonal components corresponding to an 8×8 DCT transform matrix and the remaining components corresponding to an 8×8 matrix with all elements being zero, and a transpose matrix of an M×M forward DWT transform matrix.