Abstract: The approaching object detection unit in a moving object detection apparatus for a moving picture calculates a moving distance of each characteristic point in an image frame obtained at time point t?1, on the basis of an image frame obtained at time point t and an image frame obtained at time point t?1, and on the basis of the image frame obtained at time point t?1 and an image frame obtained at time point t+m, a moving distance of a characteristic point is in the image frame obtained at time point t?1 and has a moving distance to be less than a prescribed value.

Abstract: Embodiments are described for a brightness enhancement method, system and apparatus for low power architecture. A histogram of a contrast image may be generated. One or more parameters may be set based on the histogram. A tone mapping for the contrast image may be determined based on the one or more parameters. An output pixel may be determined based on the tone mapping.

Abstract: A method, computing device, and associated computer readable storage media containing instructions for binarizing a grayscale image by manually determining a first threshold that yields optimal binarization values to one or more images in a set of images, calculating the histograms of each of the images determined using the first threshold, calculating a set of statistical parameters such as the mean, standard deviation and variance of each histogram, determining a second threshold as a function of the set of statistical parameters, and comparing each pixel of the grayscale image to the second threshold. The second threshold T may be a function of the mean m, standard deviation s and variance v and is calculated by fitting a third degree polynomial curve T=a0+a1m+a2s+a3v, where the coefficients A=[a0 a1 a2 a3]T are found using a minimum mean square error algorithm.

Abstract: According to one embodiment, an input image signal is passed through a plurality of first high pass filters having different passing frequency band to generate level histograms. High frequency component noise reduction processing is applied to the output of one of the first high pass filters selected based on one of the generated histograms that satisfies a predetermined threshold, low frequency component noise reduction processing is applied to a result obtained by subtracting the output of the selected first high pass filter from the input image signal, and outputs obtained by both the noise reduction processing are added.

Abstract: A method for automatically detecting a collimation edge or region includes reading an image captured by an X-ray imaging system, detecting intersection points between a foreground and a background and between a foreground and a tissue on the X-ray image, and performing a Hough transform or Radon transform on the detected intersection points to form collimation edge lines interconnecting the foreground and the background, and the foreground and the tissue, respectively.

Abstract: A method and apparatus for processing image pixel signals having at least two color components in which at least some of the image pixel signals are classified into a plurality of classifications and transformed by a transform function associated with the classifications.

Abstract: According to one embodiment, a correction parameter creation apparatus includes a histogram creation module and a parameter creation module. The histogram creation module is configured to create a histogram of luminance values in an input image. The parameter creation module is configured to create a parameter indicating an input-output characteristic to correct the input image by equalizing the histogram. Where the histogram creation module is configured to determine whether a target pixel in the input image is a local low-luminance pixel or not, and omit to count a frequency of a luminance value of the target pixel if the target pixel is determined to be the local low-luminance pixel.

Abstract: Systems and methods analyze the physical structure of text rows in a document image, including the positions of one or more alignments of one or more character blocks in one or more text rows of the document image. The systems and methods determine one or more groups of text rows that are placed into a class based on the structures of the text rows, such as the positions of the one or more alignments of the one or more character blocks in each text row.

Abstract: An exposure control apparatus for controlling an exposure adjustment mechanism on the basis of a captured image signal includes the following elements. A face detecting unit detects a face of a person appearing in a captured image on the basis of the captured image signal. A histogram data determining unit determines histogram data by setting a face detection region in the captured image according to detection information and detecting at least a brightness value of the face detection region from the captured image signal. A target brightness setting unit sets a target brightness range for desired brightness of the face. An exposure control amount determining unit determines, when a face is detected, an amount of control for the exposure adjustment mechanism by comparing the target brightness range with a brightness value at a peak of the histogram data or a brightness region in the vicinity of the peak.

Abstract: An image processing device for processing image data includes: a gray level transforming processing unit which receives input, of image data, performs gray level transforming, and outputs image data having all of multiple color information by each pixel being configured of one of the multiple color information; the gray level transforming processing unit further including a first gray value computing unit for computing a first gray value according to the brightness of a pixel of interest which exists in a pixel location of interest; a second gray value computing unit for computing a second gray value by gray value transforming as to the first gray value; and pixel value gray level transforming unit for computing a pixel value subjected to gray level transforming of the pixel of interest, based on the first gray value, the second gray value, and the pixel value of the pixel of interest.

Abstract: An image reading device includes a reference member, a reading unit, a first reference value setting unit, a detecting unit, a second reference value setting unit, a determining unit, and a pixel value setting unit. The reading unit obtains image data and reference data. The first reference value setting unit sets a first reference value based on the reference data. The detecting unit detects a usage state of the reading unit. The second reference value setting unit sets a second reference value in accordance with the usage state. If the determining unit determines that the first reference value is in a predetermined condition, the pixel value setting unit sets a pixel value based on the image data and the first reference value; otherwise, the pixel value setting unit sets the pixel value based on the image data and the second reference value.

Abstract: An image processing method applied in an image processor for processing an image including first pixels each having a pixel value, a first reference pixel value representing a mean value of the pixel values of the first pixels, the pixel values of the first pixels being distributed within a first distribution range bounded between a second reference pixel value and a third reference pixel value. Second pixels are selected from the first pixels. The pixel values of the second pixels are distributed within a second distribution range. The second distribution range of the second pixels is smaller than the first distribution range of the first pixels. A local characteristic of the image is obtained according to the second pixels. A parameter of the image is adjusted according to the local characteristic.

Abstract: Disclosed are an image processing method, an image processing apparatus, and an image processing program which perform appropriate gradation processing in each brightness region while gradation continuity is maintained. The image processing apparatus which applies image processing including gradation conversion processing to image data, the image processing apparatus having: an image processing section for applying image processing to the image data based on each of a plurality of different gradation conversion processing characteristics, thereby generating a plurality of image-processed image data; a synthesis ratio calculating section for calculating the synthesis ratios of the plurality of image-processed image data by referencing image information of the image data prior to image processing; and a synthesis section for synthesizing the plurality of image-processed image data based on the synthesis ratios, thereby generating image data to be outputted.

Abstract: A device of gathering statistics of the gray distribution of an image and a method thereof are provided. The device includes a comparing unit, a count unit, a memory unit, and a data allotment unit. The comparing unit determines gray information of a plurality of gray data of the input image, and output a respective count signal accordingly. The count unit includes a plurality of counters. Each counter corresponding to predetermined gray information has a count value. The counters update the count values according to the respective count signals. When the count value exceeds a predetermined value, the count unit outputs a pulse signal corresponding to the predetermined gray information. The data allotment unit updates the statistics of the gray distribution of the image stored in the memory unit according to the pulse signal. The present invention reduces the number of the registers the counters require and decreases hardware costs.

Abstract: An image having the image quality desired by a photographer is provided by minimizing overexposure or underexposure, making the dynamic range wide, and specifying an optimum brightness level for a main subject.

Abstract: The present invention aims at obtaining a high-quality video signal by reducing tone jumps. A second grayscale conversion characteristic is calculated from a video signal to which a first grayscale conversion process has been applied using a first grayscale conversion characteristic used to convert an M-bit video signal into an N-bit video signal, where M and N are integers and M is larger than N. The first grayscale conversion characteristic is corrected by using the second grayscale conversion characteristic. The first grayscale conversion process is applied to the video signal by using the corrected first grayscale conversion characteristic.

Abstract: A color image comprises color values in each of one or more color channels for each of a plurality of points, or pixels, within the image. The image is represented by rank ordering the values in the or each color channel. The image representation generated in this way is usable for automated-vision or computer-vision tasks, for example.

Abstract: The present invention aims at obtaining a high-quality video signal by reducing tone jumps. A second grayscale conversion characteristic is calculated from a video signal to which a first grayscale conversion process has been applied using a first grayscale conversion characteristic used to convert an M-bit video signal into an N-bit video signal, where M and N are integers and M is larger than N. The second grayscale conversion characteristic is corrected by using the first grayscale conversion characteristic. A second grayscale conversion process is applied to the video signal by using the corrected second grayscale conversion characteristic.

Abstract: Aspects of the disclosure provide a printing method that can utilize a lightly pigmented toner along with a darkly pigmented toner to improve the image quality. The method can include receiving a dataset corresponding to a printing of a printing system using a darkly pigmented toner. The printing system may have an undesirable optical density printing range for the darkly pigmented toner. Further, the method can include converting the dataset to a first dataset corresponding to a first printing of the printing system using the darkly pigmented toner, and a second dataset corresponding to a second printing of the printing system using a lightly pigmented toner. The first dataset can avoid the undesirable optical density printing range for the darkly pigmented toner, and a combination of the first printing and the second printing providing a substantially same printed optical density corresponding to the received dataset.

Abstract: A method performs inverse tone mapping of an image in a decoder. For each block of each color channel of the image the following steps are performed. A scaling factor is determined for a current block of the image by adding a predicted scaling factor for the current block to a difference between the predicted scaling factor and the scaling factor of an adjacent block. An offset value for the current block is determined by adding a predicted offset for the current block to a difference between the predicted offset value and the offset value of the adjacent block. The scaling factor and the offset value are applied to pixel intensity values of the current block to produce a mapped block in which a bit-depth of the mapped block is greater than the bit-depth of the current block.

Abstract: An image processor that can suitably specify a predetermined area of a grayscale image is provided. An extreme value coordinate acquiring unit performs scanning on at least one of a plurality of pixels including a target pixel from the target pixel in accordance with gradient information corresponding to a change in a pixel value, and acquires a coordinate of the scanned pixel corresponding to an extreme value of the pixel value as a coordinate of an extreme value pixel corresponding to the target pixel. An area specifying unit labels each target pixel with an area identification mark used for specifying an area to which the each pixel belongs. The area specifying unit 103 labels each of different pixels corresponding to coordinates of extreme value pixels located close to each other within a particular range with an area identification mark indicating an identity of the area to which the pixels belong.

Abstract: The invention provides image display panels. The image display panel comprises a histogram generator, a tone slope generator, and an image transformer. The histogram generator receives an original image, counts the pixels of different gray levels to generate a histogram distribution of the original image, and compares the pixel counts at every gray level with a first threshold count to identify the peaks of the histogram distribution. The tone slope generator generates a tone slope based on the histogram distribution and peaks of the histogram distribution. The image transformer transforms the original image into a modified image based on the tone slope.

Abstract: Background images are removed and only desired payment information is extracted from a grayscale image of a check or similar financial instrument. A density distribution improvement process applied to grayscale raw image data 40 acquired by scanning a check corrects the density distribution of the raw image data 40 to separate the density range of the desired payment information from the density range of the background image. A threshold level 44 for clearly separating the payment information from the background image is then calculated from the characteristics of the density distribution of the grayscale improved image data 42 acquired by the density distribution improvement process. Histograms of the density distributions are used to determine the characteristics of the density distribution. The improved image data 42 is then converted to binary image data 46 using the threshold level 44.

Abstract: In an image forming apparatus includes a quantization threshold value to convert input image data of an N value to output image data of an M value based on random dither processing. A flag to designate addition of a non-periodic component to a quantization threshold value can be set for each quantization threshold value and a threshold value that has a non-periodic component is added to the quantization threshold value based on a relation between a large and a small quantization threshold value in different threshold value levels with respect to any target pixel in the quantization threshold value.

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: The driving apparatus of a display device calculates a slope using a minimum gray, a maximum gray, a gray average of frame data in a current frame, and a gray average of frame data in a previous frame, and corrects and outputs the input frame data according to the slope, using frame data of one frame. As a result, a gray range of the input image signal can be extended, thereby improving visibility. Further, in a case of a motion picture, even when a difference of a gray range of images of adjacent frames is large, an original image is not distorted due to extension of a gray range. Also, even when noise is included in the input image signal, a gray range can be extended after removing the noise.

Abstract: Tuning sizes of cells of an interpolated lookup table may be performed based at least in part on an area specific behavior of a quality metric. A weighted input shaper curve may be determined to reduce interpolation errors in a multi-dimensional color lookup table. An initial input shaper curve may be applied to a color lookup table to create an interpolation result. The interpolation result may then be assessed for accuracy. The accuracy assessment may include comparing the interpolation result with a reference representation. An interpolation error may be calculated as the error between one or more intervals in a prospective color lookup table as compared to a reference representation. The weighted input shaper curve may be based at least in part on the calculated interpolation error.

Abstract: An image transient improvement apparatus for suppressing aliasing patterns in an image is disclosed. The image transient improvement apparatus includes a limit detector for detecting a maximum gray level and a minimum gray level of a plurality of pixels of a sub-zone of the image, a filter for acquiring a frequency component of the plurality of pixels at a specific frequency, a weighted second-order derivative detector for calculating a plurality of second-order derivatives of the plurality of pixels and accordingly generating a gain, a multiplier for multiplying the frequency component by the gain to generate an amplified frequency component, an adder for adding the amplified frequency component to the plurality of pixels to generate an adding result, and a limiter for converting the adding result to a transient improved sub-zone according to the maximum gray level and the minimum gray level.

Abstract: An image processing device includes a histogram generation unit configured to generate a density histogram on the basis of image data of an original document, a white-reference value detection unit configured to acquire as a white reference value a density value at a density distribution peak in a predetermined white side range of the density histogram, a background-removal level determination unit configured to determine a background-removal level value having the maximum density to remove a background component by using a reference table on the basis of the white reference value, and a background removal unit configured to remove the background component from the image data by using the white reference value and the background-removal level value.

Abstract: Pixel characteristics, such as whether a pixel forms part of the background of an image, are evaluated by computing histograms from pixel color space components, by comparing pixel color space components to threshold values, or by other methods.

Abstract: The grayscale of an input signal is converted without amplifying noise components thereof. A grayscale conversion portion performs grayscale conversion on an input signal IS to create a converted signal TS, a noise reduction degree determining portion determines a noise reduction degree NR that expresses a strength of noise reduction processing to be applied to the converted signal based on the input signal IS and the converted signal TS, and a noise reducing portion executes noise reduction processing on the converted signal TS based on the noise reduction degree NR. By doing this, it is possible to convert the grayscale of the input signal without enhancing the noise.

Abstract: An image processing apparatus includes a histogram calculation unit configured to calculate a histogram of a luminance value for each spatial block obtained by dividing an input image in a spatial direction, a gray scale correction coefficient calculation unit configured to calculate a gray scale correction coefficient used for correction of the gray scale of a luminance value for each bin of the histogram, and a gray scale correction unit configured to perform gray scale correction of a luminance value of a target pixel based on the gray scale correction coefficient of the bin to which the target pixel of the input image belongs and the gray scale correction coefficient of a bin adjacent to the bin to which the target pixel belongs in the spatial direction and a luminance direction.

Abstract: A medical image is reproduced after being subjected to image processing appropriate for conversion into an image suitable for interpreting. Selection of a imaging menu item from a imaging menu being displayed is accepted, and the medical image is reproduced after being subjected to the image processing for converting the image into the image appropriate for the reproduction according to the selected imaging menu item. At this time, an index value representing an anatomical characteristic is calculated from the medical image, and the most appropriate imaging menu item to be selected from imaging menu items is judged based on the index value.

Abstract: An adaptive histogram equalization-based approach improves contrast in a video signal. For each video frame, the histogram of the pixel luminance values is calculated. The calculated histogram is divided into three programmably-sized regions that are equalized independently of each other. The equalization is performed in a controlled fashion by clamping the peaks of the histogram thereby ensuring limited stretching of sharp peaks. The equalized values are averaged with the original pixel values with a weighting factor that is different for the three regions chosen such that the darker regions are enhanced more than the brighter ones. To ensure smooth enhancement, programmable guard band regions can be defined between the three divisions of the histogram. The statistics calculated from one frame may be used to enhance the next frame to eliminate the need for frame buffers. Many of the calculations may be performed in the inactive time between two frames.

Abstract: Corresponding points or a motion vector is generated with reduced positional error even if incoming images have been shot under different illumination conditions. An image processing apparatus (100, 120) includes an initial corresponding point computing section (113) for computing and outputting multiple sets of corresponding points across multiple images and a corresponding point recomputing section (104), which selects reference corresponding points, consisting of multiple sets of initial corresponding points with small error, from the multiple sets of initial corresponding points by using a photometric constraint equation and a geometric constraint equation, newly computes aimed corresponding points associated with those reference corresponding points, and then outputs the reference corresponding points and the aimed corresponding points as corresponding points.

Abstract: A method of performing non-linear transformation of a digital image for contrast modification. The original video input is compared to a linear transformation with gain and offset; and, the differential of the change in gain or slope and the input image ? is multiplied by a factor m obtained from a look-up table and the product of m and ? added to the original input to obtain the output video.

Abstract: Disclosed herein are methods and systems for dynamic color equalization that can be used for image viewer applications. The methods and systems described involve linking enhancement parameters to a changing viewport. When a large image is being viewed, only a portion of the image can fit in a viewer window at a time. A viewport can be defined as the portion of image data that is displayed on a screen. Scrolling or zooming the image can be described as moving the viewport.

Abstract: Radiometric calibration of an image capture device (e.g., a digital camera) using a single image is described. The single image may be a color image or a grayscale image. The calibration identifies and analyzes edge pixels of the image that correspond to an edge between two colors or grayscale levels of a scene. Intensity distributions of intensities measured from the single image are then analyzed. An inverse response function for the image capture device is determined based on the intensity distributions. For a color image, the radiometric calibration involves calculating an inverse response function that maps measured blended colors of edge pixels and the associated measured component colors into linear distributions. For a grayscale image, the radiometric calibration involves deriving an inverse response function that maps non-uniform histograms of measured intensities into uniform distributions of calibrated intensities.

Abstract: Embodiments of the invention are directed toward reversible/invertible and lossless, image data hiding that can imperceptibly hide data into digital images and can reconstruct the original image without any distortion after the hidden data have been extracted in various digital image formats including, but not limited to Joint Photographic Experts Group (JPEG). In particular, embodiments of the invention provide a lossless data hiding technique for JPEG images based on histogram pairs. that embeds data into the JPEG quantized 8×8 block DCT coefficients and achieves good performance in terms of peak signal-to-noise ratio (PSNR) versus payload through manipulating histogram pairs with optimum threshold and optimum region of the JPEG DCT coefficients. Furthermore, the invented technology is expected to be able to apply to the I-frame of Motion Picture Experts Group (MPEG) video for various applications including annotation, authentication, and forensics.

Abstract: Various techniques for implementing aspects of color control in display devices are disclosed. One exemplary technique includes measuring an input/output profile of a display, then applying a mathematical model to the display's measured profile to generate color control tables. One exemplary technique may include tracking a first color temperature below a high-luminosity transition point and gradually transitioning to tracking a second color temperature above the high-luminosity transition point. One exemplary technique may also include gradually transitioning from tracking a darklight color temperature below a low-luminosity transition point to tracking the first color temperature above the low-luminosity transition point. Another exemplary technique may include tracking a response curve for a specified chromaticity above a low-luminosity transition point.

Abstract: According to one embodiment of the invention, a smoothing module is configured to smooth and reduce grayscale differences in a plain area of an input digital image signal according to a collection parameter. A histogram acquisition module is configured to acquire a histogram value of the input digital image signal for one frame. A histogram value buffer module is configured to buffer histogram values for a plurality of frames. A luminance level transition detection module is configured to detect an interval during which an image gradually changes from light to dark or from dark to light, based on the histogram values for a plurality of frames, and to output the correction parameter.

Abstract: An efficient, effective and at times superior object detection and/or recognition (ODR) function may be built from a set of Bayesian stumps. Bayesian stumps may be constructed for each feature and object class, and the ODR function may be constructed from the subset of Bayesian stumps that minimize Bayesian error for a particular object class. That is, Bayesian error may be utilized as a feature selection measure for the ODR function. Furthermore, Bayesian stumps may be efficiently implemented as lookup tables with entries corresponding to unequal intervals of feature histograms. Interval widths and entry values may be determined so as to minimize Bayesian error, yielding Bayesian stumps that are optimal in this respect.

Abstract: An image contrast enhancement apparatus and method thereof are provided. The image contrast enhancement apparatus includes an image analysis module, a histogram separation unit, and a histogram adjustment unit. The image analysis module statistically analyzes pixels of an original image to produce a plurality of histogram bins and combines the histogram bins into a sub-histogram. The histogram separation unit separates each sub-histogram in every separation level into two sub-histograms in the next separation level, increases or decreases a base width of each sub-histogram such that the respective group density of two sub-histograms corresponding to the same separation point are substantially identical. The histogram adjustment unit re-distributes histogram bins of each sub-histogram or merges a portion of histogram bins of each sub-histogram in every separation level.

Abstract: A visual processing device that achieves gradation processing and further enhances a visual effect. The visual processing device 1 performs gradation processing for each image region of an input signal IS, and includes an image partitioning portion 2, a gradation transformation curve derivation portion 10, and a gradation processing portion 5. The image partitioning portion 2 and the gradation transformation curve derivation portion 10 use a brightness histogram Hm of a wide area image region Em to create a gradation transformation curve Cm of an image region Pm. The gradation processing portion 5 performs gradation processing of the image region Pm based on the derived gradation transformation curve Cm.

Abstract: An image processing method includes: inputting color image data obtained by capturing an image at a given imaging sensitivity level; and converting the color image data to a specific uniform color space determined in correspondence to the imaging sensitivity level.

Abstract: A method and apparatus for enhancing at least one of video and image quality using an exposure aware scene adaptive global brightness contrast. The method includes determining if gain control is needed utilizing Gamma corrected histogram and ancillary data, if gain control is not required, computing a set of scene adaptive tone points and blending with information from histogram equalization if needed, if gain control is required, estimating gain value and utilizing the gain value in computing the gain table, and accordingly, generating a look-up table for enhancing global brightness contrast utilizing the gain table, the tone table and the information from histogram equalization.

Abstract: There is described a system and method for automatically discriminating between different types of data with an image reader. In brief overview of one embodiment, the automatic discrimination feature of the present image reader allows a human operator to aim a hand-held image reader at a target that can contain a dataform and actuate the image reader. An autodiscrimination module in the image reader in one embodiment analyzes image data representative of the target and determines a type of data represented in the image data.

Abstract: An image data processing device for converting original data containing gradation-value data, into processed data containing multilevel-value data.

Abstract: A system and method for performing integral histogram convolution for filtering image data is disclosed. The method may include generating an initial histogram for a kernel region of an input image comprising two or more column histograms. Each histogram may include a plurality of bucket values, each representing a sum of weights associated with pixels having the same value or a count of pixels having the same value. The method may include incrementally generating a region histogram for each successive region of the image as the kernel is passed over the image and applying a convolution operation to it. Generating the new region histogram may involve merging an additional column histogram with the initial or current region histogram, and may also involve subtracting values of a preceding column histogram from the initial or current histogram. The methods may be implemented by program instructions executing in parallel on CPU(s) or GPUs.

Abstract: A system and method of contrast enhancement is disclosed. A contrast enhancement unit processes an input pixel to generate a contrast-enhanced pixel, and a delta unit subtracts the input pixel from the contrast-enhanced pixel, thereby resulting in a difference value. Multiple delayed difference values generated by a delay unit are low-pass filtered to generate a refined difference value. An adding unit adds back the refined difference value to the input pixel, thereby resulting in an output pixel that is contrast-enhanced without noise boost.