Abstract: An upscaler is disclosed that upscales each of a maximum value map, a minimum value map and an average value map to a destination resolution. A blending module generates a detail-enhanced upscaled image of the source image having the destination resolution by blending corresponding pixel values from an upscaled image of the source image with at least one of: the upscaled maximum value map and the upscaled minimum value map. The blending may be based on the strength of detected edges in the source image and further based on a comparison of each pixel value in the upscaled image with a corresponding pixel value in an average value map. A source image characteristic calculator may generate the maximum value map, the minimum value map and the average value map based on the intensity values of a source image.

Abstract: A method for detecting edges includes calculating a gradient level value for each pixel of a digital image and assigning each pixel to one of a plurality of gradient bins based on the calculated gradient level value for each pixel, the gradient bins being defined by threshold levels. One or more of the gradient bins are assigned as edge bins, and one or more of the gradient bins are assigned as non-edge bins according to the number of pixels assigned to each gradient bin. Pixels in the one or more edge bins are identified as edge pixels, and pixels in the one or more non-edge bins are identified as non-edge pixels in an edge map. The one or more gradient bins are assigned such that a minimum number of pixels are identified as edge pixels and no more than a maximum number of pixels are identified as edge pixels.

Abstract: A method is disclosed for screening color separations of a lenticular image with a lenticular frequency of the lenticular lenses needed for viewing the lenticular image. An amplitude-modulated halftone image is calculated for each of the color separations at a screen angle and at a screen frequency, the tangent of the screen angle being a rational number. For a specific color separation, a screen angle relating to the direction perpendicular to the image strips of the lenticular image is defined, a pair of whole numbers whose ratio is equal to the tangent of the screen angle is determined, and the screen frequency of the color separation is calculated as the product of the lenticular frequency and the square root of the sum of the squares of the two whole numbers.

Abstract: Disclosed herein is a method for detecting thin lines in image data. The method is performed by a processor to process contone image data. The processing includes thresholding a window of pixels established in the contone domain to generate a binary window of image data, and then determining characteristics associated with on pixels or runs of the binary data. The characteristics (start and end locations, length of on runs) are then thresholded. The processing in the contone and binary domain are used to determine if a thin line exists in the window of image data. The disclosed method produces better quality output images and reduces the addition of false lines in an image.

Abstract: A method for creating a differential gloss image includes providing first and second anisotropic halftone structures. The first and second anisotropic structures have different orientations. One of the first and second anisotropic structures is applied to image data in a first region of an image to be halftoned. The other of the first and second anisotropic structures may be applied to image data in a second region of an image to be halftoned. A mixture of the first and second anisotropic structures is applied to image data in a third region of the image to be halftoned, whereby when printed, the three regions each have a gloss characteristic which differs from that of the other two regions.

Abstract: Disclosed herein is a method for detecting thin lines in image data. The method is performed by a processor to process contone image data. The processing includes thresholding a window of pixels using a first set of thresholds established in the contone domain, and then counting and thresholding the binary pixels using a second set of thresholds. The processing in the contone and binary domain are used to determine if a thin line exists and if a pixel of interest in the window is an edge pixel that is part of a thin line. The disclosed method produces better quality output images and reduces the addition of false lines in an image.

Abstract: A method of reducing noise in an image including steps for obtaining a first value for a target pixel, obtaining a respective second value for each neighboring pixel surrounding the target pixel and having the same color as the target pixel, for each neighboring pixel, comparing a difference between said first value and said second value to a threshold value, and replacing the first value with an average value obtained from the first value and at all second values from the neighboring pixels which have an associated difference which is less than or equal to the threshold value based on a result of the comparing step.

Abstract: The present invention provides a method and apparatus for filling Doppler signal gaps. The method comprises steps of: storing Doppler signals before and after a gap; analyzing spectral characteristics of the Doppler signals to be filled; judging whether the Doppler signals are to be frequency compensated according to the spectral parameters; compensating the Doppler signals; and filling the gap by means of weighting and superposing the frequency compensated Doppler signals to be filled and the original Doppler signals before and after the gap based on the judging result. According to the method of the present invention, the Doppler signals before and after the gap are first subjected to frequency compensation, and then weighted and superposed with the acquired Doppler signals, thus obtaining a continuous spectrogram and audio output and maintaining the original spectral characteristics of the Doppler signal.

Abstract: A method for simultaneously optimizing a digital image taken in or through a scattering medium and obtaining information regarding optical properties of the scattering medium is provided. Data of the digital image is received by a computer. The digital image is evaluated according to an objective image quality metric and a resulting image quality value is compared to a previously stored image quality value for the image. A revised optical transfer function is derived by modeling the optical properties of the medium to be used to generate a restored digital image, which is derived from the original image and the revised optical transfer function. The restored digital image is evaluated according to the objective image quality metric and an optimized restored image is identified. The optical properties associated with the optical transfer function producing the optimized restored image are retrieved and represent a close approximation of the true optical properties of the medium.

Abstract: An image analyser analyses regions of an image. An image scaler may then scale the image adaptively, in dependence on the nature of region of the image being scaled. In one embodiment, adjacent pixels are analysed to determine their frequency content. This frequency analysis provides an indication of whether the pixels likely contain hard edges, discontinuities or variations typical of computer generated graphics. As a result of the analysis, the type of scaling suited for scaling the image portion containing the pixels may be assessed. Adjacent pixels having high frequency components may be scaled by a scaling circuit that introduces limited ringing. Adjacent pixels having lower frequency components may be scaled using a higher-order multi-tap scaler. Resulting scaled pixels may be formed as a blended combination of the two different scaling techniques.

Abstract: An object detection system is disclosed in at least one embodiment. The system includes a far IR sensor operable to sense thermal radiation of objects and surroundings in a field of view and to generate a far IR image in response thereto, and an image processing device operable to receive and process the far IR image to detect the presence of one or more objects in the field of view. The image processing device can be configured to process the far IR image by generating an initial threshold image based on the far IR image and an initial threshold value, iteratively obtaining a number of successive threshold images based on the far IR image and a number of successively increased threshold values, and determining the presence of one or more objects in the field of view based on the threshold images and threshold values.

Abstract: A detection unit which includes an image display panel, brightness averaging unit, scene changeover detection unit, and brightness suppression unit in order to provide an image display apparatus having an ABL that does not give the observer any visual sense of incompatibility without increasing the circuit scale determines the presence/absence of a scene changeover on the basis of the frame differential or second order differential of the average brightness. If a scene changeover takes place, the display brightness is changed quickly, and if no scene changeover occurs, changed slowly.

Abstract: Provided are an apparatus and method of measuring a distance using structured light. The apparatus includes a binarization unit binarizing an image, an image identification unit identifying an image having connected pixels in the binarized image, a length ratio calculation unit obtaining the length ratio of the major axis of the image having the connected pixels to a minor axis perpendicular to the major axis, a pixel mean calculation unit obtaining the mean of pixel values of the image having the connected pixels, and an image extraction unit extracting an image formed by the light irradiated from the light source, from the images having connected pixels using the length ratio and the mean of the pixel values.

Abstract: In the image pickup system of the present invention, factors that have an effect on noise such as the signal level, temperature of the CCD during shooting, exposure time, gain and the like are dynamically acquired, the noise level of the CCD is estimated, for example, for each pixel by a noise estimating unit, and signal components equal to or less than this noise level in the video signals are suppressed by a noise reducing unit, so that a high-quality image that is substantially free of noise is obtained while preserving the edges of the image and the like.

Abstract: A tone dependent green-noise error diffusion method includes setting a first threshold and a second threshold, and determining a two-level value of a color level of an input image according to the first threshold and the second threshold; subtracting the two-level value from the color level value to generate an error value; performing an error diffusion on the error value to generate an error diffusion accumulation value; adjusting the color level according to the error diffusion accumulation value; performing a hysteresis filtering on the two-level value to generate an output dependent feedback value; and adjusting the color level according to the output dependent feedback value.

Abstract: Methods of determining the divergence angle between a primary image and a secondary image generated by a glazing are disclosed. In a first method, a glazing is illuminated with a light source and a primary and a secondary image of the light source, generated by the glazing, are captured using an image capture device. The distance between the primary and the secondary image is determined, and the divergence angle determined from this distance. In a second method, the primary and secondary images are viewed on a target marked with a scale indicating the divergence angle. The divergence angle is read from the scale and the positions the primary and secondary image. In this second method, the light source is located at the center of the target. In both methods, the light source comprises at least one light emitting diode. Preferably, the method is used to examine the edge region of a glazing.

Abstract: The present invention relates to an image processing method, an image processing apparatus and an image processing program for dealing with inverted characters (outlined characters) constituted by white pixels on a black ground in a tree structure same as that of normal characters constituted by black pixels on a white ground. In the present invention, black pixel blocks and white pixel blocks are sampled recursively from a binary image, tree structure data indicating a positional relation between the sampled black pixel blocks and white pixel blocks is created, an inverted image is created by white-black-inverting the insides of black pixel blocks that can include inverted characters, of black pixel blocks included in the tree structure data, white pixel blocks and black pixel blacks are sampled from the created inverted image, and data regarding the sampled white pixel blocks and black pixel blocs is added to corresponding nodes of the tree structure data.

Abstract: A method may include the steps of segmenting an image into a plurality of tiles, calculating an upper clip limit and a lower clip limit for each tile of the plurality of tiles based upon a user input standard deviation, generating a lookup table for each tile of the plurality of tiles by linearly mapping the pixels of the image based upon the calculated upper clip limit and lower clip limit, processing each tile of the plurality of tiles based upon the generated lookup table, and generating a processed image by combining each of the processed tiles. The method may include the steps of scaling the image between zero and one and/or scaling the image based upon the display type. The method may be stored on a computer readable medium and may be used in an image processing system having memory, a processor, and a display.

Abstract: A method of enhancing details in an input image. The input image comprises input pixels, which have input pixel values (IPV) limited to a range (RA). The method comprises average filtering (1) the input pixel values (IPV) to obtain average brightness values (LV). A luminance mask is applied (2) to the average brightness values (LV) to obtain masked values (MV) which are different for average brightness values (LV) in a sub-range (SR) of the range (RA) than for pixels outside the sub-range (SR). The input pixel values (IPV) are detail filtered (3) to obtain detail values (HV) indicative for an amount of detail. A non-linear function (NLF) is applied (5) on the input pixel values (IPV) to obtain for each input pixel value (IPV) a corresponding output pixel value (OPV). A gain of the non-linear function (NLF) is dependent on both the masked value (MV) and detail value (HV) which both are determined for the particular input pixel.

Abstract: The number of pixels in an identified pixel region is counted, a feature point of the pixel region is extracted and the number of the feature points is counted when the number of the pixels counted has been determined to be equal to or higher than a first threshold value, whether the counted number of the feature points is equal to or lower than a second threshold value is determined, features is calculated based on the feature point extracted from the pixel region when the number of the feature points has been determined to be above the second threshold value, and the first threshold value is changed when the number of the feature points has been determined to be equal to or lower than the second threshold value. Image similarity determination process can be stably performed without any degradation in determination accuracy.

Abstract: A system and method to automatically detect, track and count individual moving objects in a high density group without regard to background content, embodiments performing better than a trained human observer. Select embodiments employ thermal videography to detect and track even those moving objects having thermal signatures that are similar to a complex stationary background pattern. The method allows tracking an object that need not be identified every frame of the video, that may change polarity in the imagery with respect to background, e.g., switching from relatively light to dark or relatively hot to cold and vice versa, or both. The methodology further provides a permanent record of an “episode” of objects in motion, permitting reprocessing with different parameters any number of times. Post-processing of the recorded tracks allows easy enumeration of the number of objects tracked with the FOV of the imager.

Abstract: An image processing method for deriving text characteristic images from an input image includes: performing a plurality of edge detecting processes upon the input image to generate a plurality of edge images, respectively, and deriving a first text characteristic image according to the edge images. The image detecting processes include: performing a first edge detecting process upon the input image to derive a first edge image according to a first upper threshold and a first lower threshold, and performing a second edge detecting process upon the input image to derive a second edge image according to a second upper threshold and a second lower threshold.

Abstract: A method for improving image quality of edge pixels, when separating an image signal into a set of image planes is provided. The method includes searching for a minimum value and a maximum value within at least one predefined neighborhood pixel window centered on a current pixel in the image signal; and conditionally switching the edge pixels to either the minimum value or the maximum value in the foreground and background planes respectively, or to a value of a specified characteristic of the current pixel, based on predetermined criteria. One such predetermined criteria for this conditional switching of the edge pixels comprises comparing the minimum or maximum luminance values in the predefined neighborhood window of the current pixel and their corresponding chrominance values to some predetermined thresholds which are characteristic of the image for the foreground and background planes, respectively.

Abstract: Included are: a prefilter (101) for outputting, based on filter characteristics control data, predetermined frequency components in an input video signal as current image data; encoding means (116) for subjecting the current image data to an encoding process, and outputting encoding parameters together with a bit stream corresponding to current image data as a result of the encoding process; and filter control means (117) for outputting the filter characteristics control data that is set based only on one or two of the encoding parameters.

Abstract: In a solid-state image pickup apparatus having a pixel array unit composed by two-dimensionally arranging pixels for detecting a physical quantity in a row-column manner, pixel signals of a plurality of systems having different sensitivities are read from the pixel array unit in an analog manner, the pixel signals of the plurality of systems are amplified at respective basis amplification rates when a gain setting of the analog pixel signals is lower than a predetermined gain, and a pixel signal of at least one system having a high sensitivity among the plurality of systems is amplified at a plurality of amplification rates including an amplification rate higher than a basis amplification rate of the system having the high sensitivity when the gain setting is equal to or higher than the predetermined gain.

Abstract: Systems, methods, and devices for applying lens shading correction to image data captured by an image sensor are provided. In one embodiment, multiple lens shading adaptation functions, each modeled based on the response of a color channel to a reference illuminant, are provided. An image frame from the image data may be analyzed to select a lens shading adaptation function corresponding to a reference illuminant that most closely matches a current illuminant. The selected lens shading function may then be used to adjust a set of lens shading parameters.

Abstract: Thresholding gray-scale images to produce bitonal images. In one example embodiment, a method for thresholding a gray-scale image to produce a bitonal image includes several acts. First, a first portion of gray-scale pixels of the gray-scale image are thresholded based on a global threshold and edge strength information. Next, a second portion of the gray-scale pixels are thresholded based on the global threshold and local pixel information. Finally, a third portion of the gray-scale pixels are thresholded based on a local threshold.

Abstract: A method for an image adjustment is disclosed. The method comprises the steps of: reading an interested pixel and its plural neighboring pixels from an image storage device; determining a so-called first gradient value of the first direction and a so-called second gradient value of the second direction, wherein the first direction is the orthogonal direction of the second direction; comparing the first and the second gradient values; executing a sharpness adjustment to the interested pixel along the direction which has larger gradient value; then executing a noise reduction or smoothing adjustment to the interested pixel along the direction which has smaller gradient value; and repeating the steps until all interested pixels are processed and obtaining a new pixel value.

Abstract: A method and apparatus, particularly suited to SIMD instruction sets, to filter streaming video information encoded under a predictive encoding algorithm specified under video encoding standards, such as MPEG 4 or H.264/AVC. The filtering operation de-blocks or removes unwanted borders in the perceived video. During the filtering process, a series of filtering mask is generated based on temporal and spatial statistics of predictive encoded video information, which is then recursively applied to the video in order to gate filtered or unfiltered video to an output channel according to coefficients of the masks. The filtering mask effectively yields a decision or rule-based map that transforms the video on a pixel-by-pixel basis thereby avoiding complex and processor-intensive decision tree logic customarily required to process individual pixels of successive macroblocks that may have different filtering requirements.

Abstract: This disclosure relates to decreasing the required buffer memory capacity while reducing the impact of an arithmetic error in error diffusion processing. A quantization circuit (4) quantizes input image data and outputs an output code. The quantization error generated in the quantization circuit (4) is calculated by an inverse quantization circuit (5) and subtracter (6). The calculated quantization error is stored in a buffer (8). Since the buffer (8) only needs to have a size capable of storing the quantization error, the size can be made smaller than before. A diffusion filter (9) diffuses the quantization error using a quantization error or the like, which is stored in the buffer (8). A latch (3) and bit connector (1) can usefully reduce the impact of an arithmetic error in error diffusion processing on the next input image data.

Abstract: In an image-processing apparatus having a capability of performing region distinction processing and an image region discrimination processing method, a first region distinction unit uses a previously set threshold value for an image region distinction to perform a region distinction processing of a character and a non-character on image data read from an original document, an edge feature amount image and a character determination signal are obtained, a second region distinction unit makes a region distinction on the edge feature amount image based on the threshold value and generates and displays sub-region images obtained by dividing the edge feature amount image into plural parts, a character discrimination strength adjustment is performed on a display screen while each of the sub-region images is visually identified, the correction parameter is reflected in the edge feature amount image, and the region distinction processing is performed again.

Abstract: An image processing apparatus is configured to apply correction processing to image data having sharpness varying depending on an alignment direction of pixels. The image processing apparatus detects a feature quantity in an edge direction of the image data. The image processing apparatus sets an intensity of the correction processing based on correction intensity which is predetermined based on the sharpness varying depending on the alignment direction of the pixels, according to the detected feature quantity in the edge direction of the image data.

Abstract: A noise eliminating device may include a noise eliminating mechanism that eliminates an isolated noise in an image being photographed. The noise eliminating mechanism may include a noise pixel detection mechanism and a pixel correction mechanism. The noise pixel detection mechanism may detect a noise pixel by scanning the image. The pixel correction mechanism may correct a level of a detected noise pixel based on a level of a pixel located in a predetermined area from the noise pixel. A noise eliminating method for eliminating an isolated noise in an image being photographed may include detecting a noise pixel by scanning the image and correcting a level of the detected noise pixel based on a level of a pixel located in a predetermined area away from the noise pixel.

Abstract: An image quality adjusting apparatus includes: an output module configured to alternately output, in time division, first and second frame-rate-converted frame images that are obtained by converting first and second input frame images to increase a frame rate, respectively; a detecting module configured to detect features of each of the first and second input frame images; and an image quality adjusting module configured to perform an image quality adjustment on the first frame-rate-converted frame image based on the detected features of the first input frame image and performing an image quality adjustment on the second frame-rate-converted frame image based on the detected features of the second input frame image.

Abstract: A homogeneous region detector of an image using an adaptive threshold, and a method of the same. The homogeneous region detector includes a global region standard deviation calculation part to calculate a global region standard deviation of a whole region of an input image, a local region standard deviation calculation part to divide the input image into a predetermined number of local regions and to calculate a local region standard deviation of the each local region, and a homogeneous region determination part to separate the homogeneous region from a feature region in the input image using an adaptive threshold calculated based on entropy of the input image. Accordingly, the homogeneous region can be precisely detected by effectively separating the homogeneous region from the feature region of the input image by using the threshold adaptively calculated based on the entropy of the input image, so that the homogeneous region can be applied to various fields of image processing.

Abstract: Brightness and color tone shift distortion of captured images by a non-ideal lens can be compensated by applying an inverse transfer function to the captured image. An estimate of the lens transfer function can be measured based on a radius from a center of the lens. The lens transfer function can be measured by capturing a flat field image. The center of the lens can be determined based on a relative brightness maximum. The relative brightness of the captured flat field image can then be measured as a function of radius to generate a lens response curve. Separate response curves can be measured for each color component. A correction curve can be determined as the inverse of the response curve. The correction curve can be applied to subsequent captured images to compensate for lens degradation.

Abstract: An object of the present invention is to provide an image processing apparatus capable of obtaining a sharp image having less noise, comprising: a horizontal edge strength calculating unit 22 for calculating an edge strength along a horizontal direction of a concerned pixel; and a prefilter 24 for carrying out a filter processing based on the horizontal edge strength, and performing noise reduction and edge enhancement, a vertical edge strength calculating unit 23 for calculating an edge strength along a vertical direction of the concerned pixel; and a prefilter 25 for carrying out a filter processing based on the vertical edge strength, and performing noise reduction and edge enhancement, thereby enabling to sharpen image data in the vicinity of the concerned pixel respectively along horizontal and vertical directions, and obtain an image having less noises as well as sharp for edge directions.

Abstract: A method to assess signal transmission quality and the adjust method thereof are proposed. First, different time points of a control signal at a receiving end are acquired and the number of signal transitions in a predetermined time interval is counted. Next, the number of signal transitions is recorded and compared to a reference value to obtain a comparison result. The quality of the control signal is then determined based on the comparison result. The parameter setting of the receiving end is adjusted according to the quality of the control signal received by the receiving end to get a better performance setting.

Abstract: Video frames that contain text areas are selected from given video frames by removing redundant frames and non-text frames, the text areas in the selected frames are located by removing false strokes, and text lines in the text areas are extracted and binarized.

Abstract: A method of reducing noise in an image including steps for obtaining a first value for a target pixel, obtaining a respective second value for each neighboring pixel surrounding the target pixel and having the same color as the target pixel, for each neighboring pixel, comparing a difference between said first value and said second value to a threshold value, and replacing the first value with an average value obtained from the first value and at all second values from the neighboring pixels which have an associated difference which is less than or equal to the threshold value based on a result of the comparing step.

Abstract: In order to eliminate image deterioration based on the characteristics of an output device upon execution of edge emphasis processing, an image processing apparatus includes a setting unit which sets a print characteristic on the print medium, a region setting unit which sets a region, a brightness value derivation unit which derives brightness values, a first derivative derivation which derives first derivatives of the brightness values, an edge direction determination unit which determines an edge direction of brightness, an emphasis level determination unit which determines an emphasis level of a pixel value based on the first derivatives, and a replacement unit which calculates second derivatives of brightness values and replaces a pixel value of a pixel of interest based on the sign of the second derivative.

Abstract: An object of the present invention is to provide an image processing apparatus that obtains a high-quality image signal by determining an amount of noise in an optimum fashion and reducing the amount of noise. The image processing apparatus reduces a noise component contained in the image signal picked up by an image pickup element and digitized. The image processing apparatus includes a determining unit which determines whether or not a target pixel in the image signal is within a predetermined noise range for each pixel, and a noise reducing unit which reduces the noise of the target pixel based on the determination result.

Abstract: This invention provides a system and method for image signal contrast extension and overflow compensation. The system includes contrast extension and overflow compensation look-up tables, an image gray level boundary determining unit, a contrast extension unit, an overflow judging unit, and an overflow compensation unit. The image gray level boundary determining unit defines a maximum and a minimum among the gray levels of the pixels of an image signal and calculates the difference. The contrast extension unit selects corresponding parameter from the contrast extension table for contrast extension of a given image pixel. The overflow judging unit judges whether the pixels are overflowed. The overflow compensation unit compensates the pixel. When a pixel is overflowed, the overflow compensation unit selects, according to the gray level of the pixel, a corresponding overflow compensation parameter to reduce the gray level to overcome the problem of overflow.

Abstract: An image processing method and system using gain-controllable clipped histogram equalization, in which the image processing method includes the steps of as obtaining a brightness histogram, computing a mean brightness of an image signal, determining a clipping rate based on the mean brightness, determining a clipping threshold based on the clipping rate, obtaining a clipped brightness histogram by clipping frequencies exceeding the clipping threshold in the brightness histogram, obtaining a corrected brightness histogram by correcting the clipped brightness as histogram using the clipping rate as a total gain, obtaining a cumulative histogram from the corrected brightness histogram, and correcting an input image using the cumulative histogram as a transformation function. Accordingly, the clipping rate is adaptively controlled so that image contrast is enhanced.

Abstract: An image processing apparatus includes a threshold selecting unit that selects a threshold based on an input gray-scale value of the target pixel. When a degree of flexibility is defined as representing a degree of the number of pixels that can take different output values as a result of threshold processing on the pixels with the same input gray-scale value, the threshold selecting unit selects a threshold from at least two types of thresholds associated with pixel positions and having the same period and different degrees of flexibility.

Abstract: A method for imaging, including counting quanta of energy emitted into a range of angles from particles of an energy emitter distributed over a volume in a body, thereby generating a set of counts. The method further includes defining a probability distribution expression that specifies a local concentration of the particles of the energy emitter over the volume as a function of the set of counts, the function being defined in terms of respective coefficients of a plurality of different scales of the local concentration, including at least a first and a second scale. A dependence of the coefficients of the first scale on the coefficients of the second scale is specified, and the local concentration over the volume is computed by applying the probability distribution expression to the set of counts subject to the specified dependence.

Abstract: Techniques are disclosed for selectively dithering only a subset of a digital image. One or more ranges of digits are selected for dithering. Only those pixels having digits within the selected range(s) in the digital image are dithered. The image is printed after being selectively dithered. Digits may be selected for dithering if they have values within the range(s) of one or more non-monotonic regions of a printer transfer function. Dithering may be performed on the subset of the digital image by applying a nonlinear transformation is applied to the image and adding a dither pattern to the transformed image. The result is quantized, and the inverse of the nonlinear transformation is applied to the quantized image to produce a dithered image. The nonlinear transformation is constructed such that the effects of the dither pattern appear only in that subset of the image having digits in the selected range(s).

Abstract: A method, apparatus, and computer usable program code for signal-to-noise enhancement. In one illustrative embodiment, a system is provided for signal-to-noise enhancement. The system includes a rank order filter and a comparator. The comparator receives an ordered set of data values from the rank order filter. A signal averager averages a subset of data values selected from the ordered set of data values by the comparator.

Abstract: Various embodiments for image contrast enhancement are described. In one or more embodiments, adaptive contrast enhancement may be realized by performing local standard deviation (LSD) based histogram equalization. In such embodiments, luminance (Y) values of an image may be grouped into one of several luminance regions, with each luminance region defining an LSD threshold. An LSD value may be calculated for each pixel within a particular luminance region and then compared to the LSD threshold for the particular luminance region. If the calculated LSD value for a pixel is smaller that the defined LSD threshold, then the pixel is not counted as a population for histogram equalization calculation. Otherwise, the pixel is counted as one population. Other embodiments are described and claimed.

Abstract: A visual perception threshold unit for image processing identifies a plurality of visual perception threshold levels to be associated with the pixels of a video frame, wherein the threshold levels define contrast levels above which a human eye can distinguish a pixel from among its neighboring pixels of the video frame. The present invention also includes a method of generating visual perception thresholds by analysis of the details of the video frames, estimating the parameters of the details, and defining a visual perception threshold for each detail in accordance with the estimated detail parameters. The present invention further includes a method of describing images by determining which details in the image can be distinguished by the human eye and which ones can only be detected by it.