Abstract: Levels of an input video signal are detected at successive pixels. An absolute level difference is produced that is an absolute value of the difference at each pixel pair. One absolute difference is applied nonlinear processing to be subtracted from an initial value to obtain a subtracted value. An absolute value of the subtracted value is set to a predetermined value if not larger than this value. The absolute difference is obtained from a pixel pair located in the middle of the pixels. The absolute value subjected to the nonlinear processing is added to the remaining absolute differences, to obtain an evaluation value. The input signal is subjected to low-pass filtering, thus video signals being output with high-frequency components attenuated depending on filter characteristics. The input signal with no filtering applied or one of the signals applied the filtering is selected for edge enhancement depending on the evaluation value.

Abstract: An image signal is resolved into a plurality of frequency components whose spatial frequencies are different from each other; a variation component of the image signal is extracted based on each of the plurality of frequency components, an absolute value of the variation component being smaller than a predetermined reference value; a level difference amount of the image signal is calculated based on the extracted variation component; and the calculated level difference amount is subtracted from the image signal.

Abstract: A method for increasing the resolution of a frame of a video includes receiving at least three frames of the video and compensating for the motion of a portion of at least two of the frames with respect to another one of the frames. After the motion compensation, spatially processing each of the frames of the video to increase the resolution of each of the at least three frames of the video. After the spatial processing, temporally processing at least three frames to determine the increased resolution of the frame of the video, wherein the frame is one of the at least three frames of the video.

Abstract: A video-information-processing apparatus comprising: a smoothing unit to smooth input video information of a plurality of pixels and generate smoothed video information; a subtraction unit to calculate a gradation difference between the input and smoothed video information; a mixing unit to mix the input and smoothed video information at a ratio corresponding to the difference and generate mixed video information; a determination unit to determine whether or not a peripheral pixel region, including each pixel in the input video information and pixels located around the pixel, is a low-frequency region not including a gradation change greater than or equal to a predetermined gradation change; and an output-selection unit to output the mixed video information when the determination unit determines that the peripheral pixel region is the low-frequency region and output the input video information when the determination unit determines that the peripheral pixel region is not the low frequency region.

Abstract: Image quality adjustment of an inputted image signal is performed with higher accuracy to display a more preferable image to the user. An attribute information determining unit obtains first attribute information indicating the format of the inputted image signal and second attribute information indicating transmission characteristics of the image signal. An image quality adjustment value calculating unit calculates optimal image quality adjustment values for the image signal from the obtained first and second attribute information. An image processing unit adjusts the image quality of the image signal based on the optimal image quality adjustment values and then outputs the image to an image display. The second attribute information includes the bit rate, resolution, and frame rate of the image signal.

Abstract: According to one embodiment, a method is disclosed. The method includes receiving video data performing pre-filtering on the data, performing content analysis is applied to identify an area of the data, applying a two-dimensional (2-D) 2nd gradient operation to extract a high frequency component and normalizing the high frequency component related to high frequency information from a previous picture.

Abstract: A system is disclosed for reducing artifacts in images and video, such as ringing or halo artifacts. The system may include an edge detector and a gain controller. The edge detector may create an edge image used by the gain controller to create a gain image, and the gain image may be used to reduce artifacts in an image. The gain controller may, for a current pixel in the edge image, compute the maximum value of the edge image over a window containing the current pixel. The gain controller may also perform averaging to determine a maximum edge value and a current edge value, and may also use a ratio of the current edge value and the maximum edge value to determine a gain to be applied to a pixel of an image.

Abstract: A method and apparatus for improving the quality of a composite video signal and a method and apparatus for decoding the composite video signal. The method for improving the quality of the composite video signal respectively detects edges from a luminance information signal and a chrominance information signal separated from the composite video signal, detects an artifact region using the detected edges, and filters the detected artifact region. Accordingly, an artifact can be effectively removed while preserving edge information and detail information of an image to improve picture quality.

Abstract: A video noise reducer divides a signal into spatial frequency bands and derives both recursively and non-recursively filtered signals for each band. Both signals are processed non-linearly. These signals are combined in ways that vary between the bands to provide a noise signal and a detail signal. A clean video signal with all noise removed is used in the recursive loop. The output signal includes detail enhancement and may have a subjectively pleasant amount of noise added back.

Abstract: A video processing device may enhance sharpness of one or more of a plurality of view sequences extracted from a three dimensional (3D) input video stream. The plurality of extracted view sequences may comprise stereoscopic left and right view sequences of reference fields or frames. The sharpness enhancement processing may be performed based on sharpness related video information, which may be derived from other sequences in the plurality of view sequences, user input, embedded control data, and/or preconfigured parameters. The sharpness related video information may enable classifying images in the 3D input video streams into different regions, and may comprise depth related data and/or point-of-focus related data. Sharpness enhancement processing may be performed variably on background and foreground regions, and/or on in-focus or out-of-focus regions. A 3D output video stream for display may be generated from the plurality of view sequences based on the sharpness processing.

Abstract: A resolution enhancing method of a video includes reducing a training video, extracting a high-frequency component from the training video, calculating a first feature vector including a feature amount of a first spatio-temporal box in the reduced video, storing pairs of the first feature vectors and second spatio-temporal boxes in the high-frequency component videos at the same positions as those of the first spatio-temporal boxes, expanding an input video, retrieving a first feature vector similar to a second feature vector including a feature amount of a third spatio-temporal box of an object of the input video to be processed, as an element, and adding a second spatio-temporal box making a pair with the retrieved first feature vector to a fourth spatio-temporal box in the expanded video at the same position as that of the third spatio-temporal box in order to generate an output video.

Abstract: A video processing device includes an input to receive pixel values for a set of pixels comprising a pixel window substantially centered around a select pixel that initially has a first pixel value. The video processing device further includes a first filter unit to determine a horizontal transient improvement value based on non-linear filtering of the pixel values in a horizontal direction, a second filter unit to determine a vertical transient improvement value based on non-linear filtering of the pixel values in a vertical direction, a third filter unit to determine a first diagonal transient improvement value based on non-linear filtering of the pixel values in a first diagonal direction, and a fourth filter unit to determine a second diagonal transient improvement value based on non-linear filtering of the pixel values in a second diagonal direction that is perpendicular to the first diagonal direction.

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: According to one embodiment, a method is disclosed. The method includes receiving video data performing pre-filtering on the data, performing content analysis is applied to identify an area of the data, applying a two-dimensional (2-D) 2nd gradient operation to extract a high frequency component and normalizing the high frequency component related to high frequency information from a previous picture.

Abstract: In an X-Y conversion chart, a threshold Th is defined as Y=0, that is, the threshold Th is defined on the X axis, a range from ?Th to +Th is defined as a range in which smoothing (noise elimination) processing is performed, and a range outside the range from ?Th to +Th is defined as a range in which sharpening processing is performed. As shown in equations in drawings, among equations denoted by Y1 and Y2 which are expressed by two linear straight lines, intersections of both the equations Y1 and Y2 are set to the maximum value and the minimum value of an X-Y conversion equation in this case. In addition, the threshold is expressed by an intersection of Y2 and the X axis. This conversion algorithm is formed by only three factors of: a coefficient ? indicating the strength of smoothing; a coefficient ? indicating the strength of sharpening; and a threshold Th on the X axis for determining switching between the smoothing processing and the sharpening processing.

Abstract: An edge adaptive de-interlacing apparatus and method are disclosed. The edge adaptive de-interlacing apparatus includes a complexity detection module, a qualifier, a comparator and a mixer. The complexity detection module detects complexity associated with a target pixel. The qualifier is coupled to the complexity detection module for generating similarity of at least one possible edge angle in response to the complexity. The comparator is coupled to the qualifier for comparing the similarity of the at least one possible edge to select a preferred edge angle. The mixer is coupled to the comparator for generating pixel data of the target pixel according to the preferred edge angle.

Abstract: An edge adaptive de-interlacing apparatus and method are disclosed. The edge adaptive de-interlacing apparatus includes a complexity detection module, a qualifier, a comparator and a mixer. The complexity detection module detects complexity associated with a target pixel. The qualifier is coupled to the complexity detection module for generating similarity of at least one possible edge angle in response to the complexity. The comparator is coupled to the qualifier for comparing the similarity of the at least one possible edge to select a preferred edge angle. The mixer is coupled to the comparator for generating pixel data of the target pixel according to the preferred edge angle.

Abstract: An image deblocking filter comprises an instruction memory. A decision unit executes instructions stored in the instruction memory to decide a first path or a second path of instruction fetching from the instruction memory to an execution unit. The execution unit is operable to execute a first instruction in the decided path the in one clock cycle. The first instruction represents a complex of three arithmetic operations and two bitwise operations for three variable operands and two constant operands. The first and second paths respectively realize deblocking formulae of a first and a second image compression standard.

Abstract: A request recognition section (373) recognizes an input operation for a source switching request to switch broadcast program contents extracted from broadcast waves to contents recorded in a recording and reproducing apparatus to display the contents on a display unit (350). Values of a plurality of setting factors such as brightness, contrast, and black level related to picture quality, which correspond to the source to be switched, specified corresponding to the previous contents source are read from a memory (360). Predefined values of the setting factors set corresponding to the previous contents source are compared with values newly read, and the values of the respective setting factors are sequentially changed stepwise. It is possible to prevent a flicker on a screen caused by a sudden change in the picture quality during processing of changing the picture quality, thereby favorably adjusting the picture quality.

Abstract: According to one embodiment, a video processing apparatus includes a histogram generator, a determination module and a sharpening processor. The histogram generator generates a histogram based on a luminance level of pixels of a video signal. The determination module determines whether the video signal is a captured video based on the histogram. The sharpening processor sharpens the video signal based on an imaging model function in which a blur due to imaging is not considered, if the video signal is not the captured video.

Abstract: According to one embodiment, a video processing apparatus includes an input module and a video processor. The input module is configured to input a video signal. The video processor is configured to apply sharpening processing to pixels in a horizontal direction and pixels in a vertical direction, which are included in the video signal, and to apply image blur correction to the pixels in the horizontal direction and the pixels in the vertical direction based on an imaging model function.

Abstract: In accordance with the teachings described herein, systems and methods are provided for enhancing the image quality of video. One or more filters may be used to filter a received video signal to generate a vertical filtered output, a horizontal filtered output and a diagonal filtered output. One or more amplification components may be used to apply separate gains to each of the vertical, horizontal and diagonal filtered outputs to generate a vertical enhancement signal, a horizontal enhancement signal and a diagonal enhancement signal. One or more summation components may be used to combine the vertical, horizontal and diagonal enhancement signals with the video signal to generate an enhanced video signal.

Abstract: An image processing apparatus includes an image quality correction circuit for correcting an image quality of input video data by enhancing the input video data and a control circuit for controlling the image quality correction circuit. The control circuit detects a signal level of a high-frequency component of the input video data and controls the image quality correction circuit in response to the signal level detection result so that the degree of enhancement of the input video data is increased in response to an increase in the signal level of the high-frequency component.

Abstract: It is possible to inhibit side effects even when an image that has sharp edge regions has been input, using a spatial processing portion (10) outputting surrounding image information US from an input image signal, a control signal generation portion (40) outputting an effect adjustment signal MOD according to a degree of flatness of an edge proximal region, and an effect adjustment portion (20) outputting a synthesized signal MUS that is synthesized by changing a ratio of the image signal IS and the surrounding image information US according to the effect adjustment signal MOD. Further, the side effects are inhibited using a visual processing portion (30) visually processing the image signal IS based on the synthesized signal MUS and the image signal IS.

Abstract: A method for deinterlacing a picture is disclosed. The method generally includes the steps of (A) generating a plurality of primary scores by searching along a plurality of primary angles for an edge in the picture proximate a location interlaced with a field of the picture, (B) generating a plurality of neighbor scores by searching for the edge along a plurality of neighbor angles proximate a particular angle of the primary angles corresponding to a particular score of the primary scores having a best value and (C) identifying a best score from a group of scores consisting of the particular score and the neighbor scores to generate an interpolated sample at the location.

Abstract: In order to inhibit artifacts (even when a special image has been input) a visual processing device is provided with a spatial processing portion extracting surrounding image information US from an input image signal IS, and a special image detection portion outputting a special image effect adjustment signal DS according to a degree of a statistical bias of the image signal IS. The visual processing device also includes a continuous changing portion outputting an effect adjustment signal MOD in which the special image effect adjustment signal DS is continuously changed between frames, an effect adjustment portion outputting a synthesized signal MUS in which the effect of the visual processing differs depending on the effect adjustment signal MOD, and a visual processing portion outputting a processed signal OS obtained by visually processing the image signal IS based on the image signal IS and the synthesized signal MUS.

Abstract: A visual processing device, display device, visual processing method, program, and integrated circuit that change a strength of visual processing of an image in real-time. A spatial processing portion (2) creates an unsharp signal US from an input signal IS. A target level setting portion (4) sets a predetermined target level value L for setting a range according to which the strength of the visual processing is adjusted. An effect adjustment portion (5) creates a synthesized signal MUS by synthesizing the predetermined target level value L and the unsharp signal US in accordance with an effect adjustment signal MOD that has been set externally. A visual processing portion (3) outputs an output signal OS in accordance with the input signal IS and the synthesized signal MUS, making it possible to change the strength of the visual processing.

Abstract: It is possible to inhibit side effects, even when an image that has sharp edge regions has been input, using a spatial processing portion (10) outputting surrounding image information US from an input image signal, a control signal generation portion (40) outputting an effect adjustment signal MOD according to a degree of flatness of an edge proximal region, and an effect adjustment portion (20) outputting a synthesized signal MUS that is synthesized by changing a ratio of the image signal IS and the surrounding image information US according to the effect adjustment signal MOD. Further, the side effects are inhibited using a visual processing portion (30) visually processing the image signal IS based on the synthesized signal MUS and the image signal IS.

Abstract: Circuits, methods, and apparatus for measuring a video signal's noise level. The determination can be made based on pixel values for a single video image frame, for example, by comparing pixel color values, luminance, or other parameter for a first and second group of pixels in the frame. Each group of pixels may be part of a line in the frame, and several such measurements may be made along each line of the frame. These measurements can then be further refined depending on the measure noise level. Once a video noise level is determined, a decision on how to further process the video signal can be made. For example, the picture can be filtered or sharpened. The amount of noise filtering can be made dependent on the amount of noise measured.

Abstract: A method of selectively sharpening video data may include, for at least some pixels in the video data, generating a sharpened value for a pixel value in an image. The sharpened value may be disregarded if a combination of the pixel value and the sharpened value is in a coring region. The sharpened value also may be disregarded if a combination of the pixel value and the sharpened value is a clipping region. The combination of the pixel value and the sharpened value may be output if the combination is not in the coring region or in the clipping region.

Abstract: Certain disclosed implementations use digital image processing to reduce the differential resolution among separations or images in film frames, such as, for example, red flare. A location in the red image may be selected using information from another image. The selected location may be modified using information from that other image. The selection may include comparing features of an edge in the first image with features of a corresponding edge in the other image. The modification may include performing wavelet transformations of the two images and copying certain coefficients (or a function of these coefficients) produced by the application of the transformation to the second image to the coefficients produced by the application of the transformation to the first image. The copied coefficients may be correlated with the selected location. Other disclosed techniques vary from the above and may be applied to other fields.

Abstract: A contour correction circuit according to the present invention determines, for a CVBS signal (a), a correction range of an edge of an image, and changes a contour component correction coefficient in a WINDOW in accordance with a state of a quality of the image, thereby solving a problem of overshoot caused at an edge of a video screen, performing optimum contour correction without excessive contour correction on a video image border part, and increasing the sharpness of the image.

Abstract: An image enhancing system uses a perfect reconstructing filter to process image signals within a specified resolution and enhance the image signals. The image enhancing system includes an image-signal-obtaining unit, a first-signal-group processing unit, a high-pass/low-pass-image obtaining unit, a brightness-adjusting unit, a threshold unit, an amplifying unit, an adder and a normalizing unit. The image-signal-obtaining unit obtains nine image signals from three lines of image signals. The first-signal-group processing unit processes the nine image signals. The high-pass/low-pass-image obtaining unit obtains a high-frequency image signal and a low-frequency image signal. The brightness-adjusting unit adjusts the brightness of the low-frequency image signal. The threshold unit processes the noise of the high-frequency image signal. The amplifying unit amplifies the high-frequency image signal. The adder adds the high-frequency image signal and the low-frequency image signal.

Abstract: An image scaling system includes a single set of line buffers that receive and store input image pixel data in an input video frame. The scaling system also includes a linear two-dimensional sharpness enhancement unit configured to receive input pixel data from the line buffers and to generate sharpened pixel data by enhancing high frequency components of the input pixel data at an input image resolution, a linear two-dimensional image scaling unit configured to receive the sharpened pixel data and to convert the sharpened pixel data into scaled sharpened pixel data at an output image resolution, and a transient improvement unit configured to receive the input pixel data from the line buffers, sharpened pixel data and scaled sharpened pixel data to improve transient responses at edges in an output image, and to generate output image pixel data at the output image resolution.

Abstract: The present invention provides an apparatus and corresponding method for reducing temporal noise of a target frame and enhancing the motion of the target frame. The apparatus includes a storage device, a temporal noise reducing circuit, and a motion enhancing circuit. The storage device stores a first filtered signal of a previous frame. The previous frame is previous to the target frame. The temporal noise reducing circuit reduces temporal noise of the target frame according to the first filtered signal and an image signal of the target frame. The temporal noise reducing circuit then generates a second filtered signal of the target frame, which is stored in the storage device. The motion enhancing circuit enhances the motion of the target frame according to the first and the second filtered signals, and generates a motion-enhanced signal of the target frame.

Abstract: An apparatus, system, method, and article for enhancing video sharpness are described. The apparatus may include a media processing node to enhance sharpness of an input image. The media processing node may include a wavelet decomposition module to perform wavelet decomposition of the input image to detect and modify edge information. Other embodiments are described and claimed.

Abstract: A CPU 200 extracts ornamental image data and layout control information from an ornamental image file FF. When the layout control information does not include characteristic values, the CPU 200 analyzes the ornamental image data to acquire characteristic values representing a tendency of image quality of the ornamental image data. The CPU 200 may additionally compute correction rates for correcting values of image quality-relating parameters of objective image data from the acquired characteristic values of the ornamental image data. The CPU 200 writes either the acquired characteristic values or the computed correction rates into the layout control information. The layout control information including the acquired characteristic values or the computed correction rates is output together with the ornamental image data in the form of the ornamental image file FF.

Abstract: Selective Sharpening May Involve Sharpening Only Certain Portions Of an Image Or a certain percentage of the pixels of an image while avoiding over-sharpening already sharp areas and the introduction of signal noise in naturally uniform color and/or sharpness areas. A selective sharpening tool may selectively sharpen the image based on a user-indicated sharpening limit. For example, the user may select a particular portion of an image and specify that the least sharp 30% of the pixels in the selected image portion should be sharpened. In response, the selective sharpening tool may determine a sharpness value for each pixel in the image, rank each pixel based on its sharpness value and sharpen only the least sharp 30% of the pixels. Thus, a user may selectively sharpen a certain portion of an image (such as based on percentage of the pixels) while avoiding overly sharpening already sharp areas.

Abstract: A video decoder comprising a first comfort noise addition block and a second comfort noise addition block. The first comfort noise addition block may be configured to (i) add comfort noise to luminance data and (ii) adjust a distribution of the comfort noise added to the luminance data. The second comfort noise addition block may be configured to (i) add comfort noise to chrominance data and (ii) adjust a distribution of the comfort noise added to the chrominance data. The first and the second comfort noise addition blocks may be integrated into a video output path of the video decoder. The distribution of the comfort noise added to the luminance data and the distribution of the comfort noise added to the chrominance data may be adjusted independently.

Abstract: An image processing device, method, an image display device and method which can obtain a high-definition display image by properly controlling processing of reducing the blur of a displayed image caused by the time integration effect of an image sensor. The image display device comprises a motion detection part (1) which detects the moving amount of an input image signal, and an edge emphasis part (2) which subjects the input image signal to edge emphasis processing, and the image display device increases an edge emphasis degree of edge emphasis processing to an area where the moving amount of the input image signal is large.

Abstract: A de-ringing device and a method thereof are provided. The de-ringing device, operative with a lookup table for storing a plurality of intensity coefficients, comprises a buffer and a de-ringing intensity determining unit. The buffer stores an input pixel sequence. The lookup table stores a plurality of intensity coefficients. The de-ringing intensity determining unit, coupled to the buffer and the lookup table, detects a plurality of pixel complexity of a first pixel group and a second pixel group associated with a target pixel in the pixel sequence, and looks up the lookup table according to the pixel complexities of the first pixel group and the second pixel group to output a de-ring intensity coefficient for the target pixel.

Abstract: An image-displaying device and a pixel control method therefore are provided. The image-displaying device includes a luminance information extraction unit which is configured to extract luminance information from an image; an image enhancement decision unit which is configured to decide an image enhancement mode based on the extracted luminance information; a pixel control unit which is configured to control a pixel of the image by the decided image enhancement mode; and an image output unit which is configured to output the pixel-controlled image. The method includes extracting luminance information from an image; deciding an image enhancement mode based on the luminance information; controlling each of a plurality of pixels of the image according to the image enhancement mode; and outputting the pixel-controlled image.

Abstract: A method is provided for block artifact detection and block artifact determination using multiple features in coded images and video. A method includes identifying a plurality of overlapping blocks in a picture with respect to a current block. Each of the plurality of overlapping blocks covers a portion of the current block and a portion of an adjacent block. The method further includes transforming at least one of the plurality of overlapping blocks into respective coefficients corresponding to at least one of a luminance component and a chrominance component. The method also includes identifying a block artifact for the at least one of the plurality of overlapping blocks when coefficients corresponding to the at least one of the plurality of overlapping blocks are larger than a predefined 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: The present invention relates to a method for filtering ringing artifacts in a reconstructed pixel edge block comprising the steps of: (a) providing said edge block; (b) determining a threshold as a function of the pixel values in said edge block; (c) mapping each pixel, of said edge block, to a corresponding binary index according to its value and said threshold; (d) scanning using a window, a first binary index of said mapped edge block and its surrounding indices; (e) determining if all entrapped binary indices of said window are uniform; (f) if not all entrapped binary indices of said window are uniform, scanning using a sub window that entraps said first binary index, within said window, for determining if all entrapped binary indices of said sub window are uniform; and (g) if all entrapped binary indices of said sub window are uniform, filtering the pixel that corresponds to said first binary index with the pixel values that correspond to the binary indices entrapped in said sub window.

Abstract: An edge detection unit performs edge detection on a frame of a moving image. A vertical line extraction unit of a block vertical boundary position detection unit extracts a vertical edge having an intensity equal to or lower than a noise determination threshold from edges detected by the edge detection unit. A vertical counter counts a total number of edges extracted by the vertical line extraction unit with respect to each pixel line position of the frame. A block vertical boundary position determination unit determines a pixel line position having a peak of a count value of the vertical counter as a block vertical boundary position. A block horizontal boundary position detection unit performs the same processing as the block vertical boundary position detection unit on a horizontal edge among edges detected by the edge detection unit and detects a block horizontal boundary position.

Abstract: A system and method for enhancing the detail edges and transitions in an input video signal. This enhancement may be accomplished by enhancing small detail edges before up-scaling and enhancing large amplitude transitions after up-scaling. For example, detail edge enhancement (detail EE) may be used to enhance the fine details of an input video signal. An edge map may be used to prevent enhancing the large edges and accompanying mosquito noise with the detail enhancement. Noise may additionally be removed from the signal. After the fine details are enhanced, the signal may be up-scaled. Luminance transition improvement (LTI) or chrominance transition improvement (CTI) may be used to enhance the large transitions of the input video signal post scaler.

Abstract: The sharpness of an image obtained by an endoscope is adjusted. A sharpness enhancement amount is determined for each pixel based on the value of each pixel which forms a luminance distribution image. Further, a portion contributing to adjustment of brightness and a portion contributing to adjustment of saturation in the sharpness enhancement amount are determined for each pixel of the image so that the sum thereof is equal to the sharpness enhancement amount. Then, an adjustment value of saturation, which is obtained by weighting the value of each pixel of the image based on the portion contributing to saturation, and an adjustment value of brightness, which is obtained by weighting the value of each pixel of the luminance distribution image, which corresponds to each pixel of the image, based on the portion contributing to brightness, are added to the value of each pixel of the image.

Abstract: A sharpness enhancing apparatus include: an edge analyzing unit configured to receive image data separated into brightness signals and color signals, and analyze an edge state by using brightness signals and color signals of cells contained in a specific area; and a sharpness correcting unit configured to calculate a sharpness correction amount by performing a mask operation on a sharpen mask, which is set according to the edge state, and the brightness signals of the cells, sum the calculated sharpness correction amount and the brightness signals of the cells, and correct sharpness of the brightness signals of the cells.

Abstract: Electronic data output from CCD is separated into a brightness component Y and color difference components Cb and Cr and an edge is extracted for each of the components. The edge amounts are calculated from the extracted edges and the component having the maximum edge amount is selected. Edge information (for example, edge gradient direction) is calculated based on the selected component having the maximum edge amount, a filter is selected based on the calculated edge information about the component having the maximum edge amount, and smoothing processing is performed for the electronic data output from the CCD based on the filter. The electronic data subjected to the smoothing processing is written into flash memory.