Abstract: A correlation value calculation device for selecting a pixel of interest within an image and a plurality of reference pixels within the image or a different image and calculating correlation values between a base block including the pixel of interest at a prescribed position and a plurality of reference blocks including each reference pixel at the prescribed position and having the same block size as the base block includes a block size determination unit, first intermediate correlation value calculation units configured to calculate correlation values in a plurality of types of block sizes, second intermediate correlation value calculation units configured to calculate correlation values in some block sizes among the plurality of types of block sizes, and a correlation value interpolation unit configured to obtain correlation values according to an interpolation.

Abstract: A correlation value calculation device for calculating a correlation value between a base block within an image and at least one reference block within the image or other image includes a pixel value distribution calculation unit configured to calculate a pixel value distribution of pixels within the image and select a range of pixel values of a large number of pixels as a valid pixel value range, a conversion coefficient calculation unit configured to calculate conversion coefficients for converting pixels of the valid pixel value range into a prescribed bit-depth, and a pixel value conversion unit configured to perform a bit-depth reduction process on pixels within the base block and pixels within the reference block on the basis of the conversion coefficients.

Abstract: An image processing device includes a computer that is configured to: detect edge-strength information expressing an edge strength in an acquired image; apply noise-reduction processing using spatial information to the image; apply noise-reduction processing using frequency information to the image; and composite a first processed image subjected to the noise-reduction processing using spatial information and a second processed image subjected to the noise-reduction processing using frequency information, by using weights in which a compositing ratio of the first processed image becomes higher than a compositing ratio of the second processed image, in a region where the edge strength, which is expressed by the detected edge-strength information, is greater than a predetermined threshold, and in which the compositing ratio of the second processed image becomes higher than the compositing ratio of the first processed image, in a region where the edge strength is less than the threshold.

Abstract: A correlation value calculation device for calculating a correlation value between a base block within an image and at least one reference block within the image or other image includes a pixel value distribution calculation unit configured to calculate a pixel value distribution of pixels within the image and select a range of pixel values of a large number of pixels as a valid pixel value range, a conversion coefficient calculation unit configured to calculate conversion coefficients for converting pixels of the valid pixel value range into a prescribed bit-depth, and a pixel value conversion unit configured to perform a bit-depth reduction process on pixels within the base block and pixels within the reference block on the basis of the conversion coefficients.

Abstract: A correlation value calculation device for selecting a pixel of interest within an image and a plurality of reference pixels within the image or a different image and calculating correlation values between a base block including the pixel of interest at a prescribed position and a plurality of reference blocks including each reference pixel at the prescribed position and having the same block size as the base block includes a block size determination unit, first intermediate correlation value calculation units configured to calculate correlation values in a plurality of types of block sizes, second intermediate correlation value calculation units configured to calculate correlation values in some block sizes among the plurality of types of block sizes, and a correlation value interpolation unit configured to obtain correlation values according to an interpolation.

Abstract: An image processing device includes a computer that is configured to: detect edge-strength information expressing an edge strength in an acquired image; apply noise-reduction processing using spatial information to the image; apply noise-reduction processing using frequency information to the image; and composite a first processed image subjected to the noise-reduction processing using spatial information and a second processed image subjected to the noise-reduction processing using frequency information, by using weights in which a compositing ratio of the first processed image becomes higher than a compositing ratio of the second processed image, in a region where the edge strength, which is expressed by the detected edge-strength information, is greater than a predetermined threshold, and in which the compositing ratio of the second processed image becomes higher than the compositing ratio of the first processed image, in a region where the edge strength is less than the threshold.

Abstract: A similarity calculation unit calculates a similarity between pixel values of a target pixel and a reference pixel and a similarity between the pixel value of the target pixel and an average value of pixel values of reference pixels, in an input image. A weighting factor calculation unit calculates weighting factors based on the calculated similarities. A weighted average value calculation unit calculates weighted average values of the pixel value of the reference pixel and the average value of the pixel values of the reference pixels by use of the calculated weighting factors. A subtraction unit calculates a difference value between the pixel values of the target pixel and the reference pixel. An isolation degree calculation unit calculates an isolation degree based on the calculated deference value. A correction unit corrects the target pixel based on the calculated isolation degree.

Abstract: A similarity calculation unit calculates a similarity between pixel values of a target pixel and a reference pixel and a similarity between the pixel value of the target pixel and an average value of pixel values of reference pixels, in an input image. A weighting factor calculation unit calculates weighting factors based on the calculated similarities. A weighted average value calculation unit calculates weighted average values of the pixel value of the reference pixel and the average value of the pixel values of the reference pixels by use of the calculated weighting factors. A subtraction unit calculates a difference value between the pixel values of the target pixel and the reference pixel. An isolation degree calculation unit calculates an isolation degree based on the calculated deference value. A correction unit corrects the target pixel based on the calculated isolation degree.

Abstract: An image processing apparatus includes a first pixel output variation detecting section, a second pixel output variation detecting section, and a pixel correcting section. The first pixel output variation detecting section detects a variation between pixel outputs of the phase difference detecting pixel and the imaging pixel of the same color as the phase difference detecting pixel. The second pixel output variation detecting section detects a variation in pixel output between imaging pixels positioned in vicinities of the phase difference detecting pixel and the imaging pixel used by the first pixel output variation detecting section. The pixel correcting section corrects the pixel output of each phase difference detecting pixel based on results of the first and second pixel output variation detecting sections.

Abstract: An image processing apparatus includes a first pixel output variation detecting section, a second pixel output variation detecting section, and a pixel correcting section. The first pixel output variation detecting section detects a variation between pixel outputs of the phase difference detecting pixel and the imaging pixel of the same color as the phase difference detecting pixel. The second pixel output variation detecting section detects a variation in pixel output between imaging pixels positioned in vicinities of the phase difference detecting pixel and the imaging pixel used by the first pixel output variation detecting section. The pixel correcting section corrects the pixel output of each phase difference detecting pixel based on results of the first and second pixel output variation detecting sections.

Abstract: Nonlinear image filter defined by local edge intensity and slope and is useful noise and artifact removal during image processing; applications include digital still cameras and video cameras.

Abstract: An image filtering method, apparatus and system, wherein the method comprising the steps of detecting at least one portion of an edge, wherein the portion of the edge provides an indication that ringing artifact are probable; subjecting at least one portion of a pixel, related to the at least a portion of the edge, to a low pass filter to produce a filtered pixel; and blending the filtered pixel with a value relating to the filter prior to filtering to produce a filtered image.

Abstract: Interlaced-to-progressive conversion with (1) 3-2 pulldown detection, (2) pre-filtering for field motion detection, (3) field motion detection with feedback, (4) field edge detection including direction angle detection by comparison of pixel differences with sets of more than pairs of pixels and a lateral edge detection probability by a lack of non-lateral angle detection, and (5) blending moving pixel interpolation and still pixel interpolation using field uniformity.

Abstract: Pre filtering is commonly used in video encoding to remove undesirable noise from video sources. Without a pre filter, the noise degrades the performance of a video encoder by wasting a number of bits to represent the noise itself, and by introducing encoding artifacts such as blocking and ringing noise. However, excess use of pre filtering will degrade subjective visual quality. This invention employs an automatic pre filter control using a subjective noise detector capable of measuring noise that strongly correlates to subjective video quality.

Abstract: A method of motion vector estimation for video encoding is provided that includes estimating a global motion vector for a sequence of macroblocks in a frame and estimating a motion vector for each macroblock in the sequence of macroblocks using the global motion vector to offset reference data for each macroblock.

Abstract: Preprocessing for motion-compensated video encoding such as MPEG includes lowpass filtering, temporal (310) and/or spatial (312), locally per pixel in response to motion vector analysis and prediction error (304) and temporal change (306). This de-emphasizes image areas of rapid change which corresponds to human perception de-emphasis.

Abstract: An image filtering method, apparatus and system, wherein the method comprising the steps of detecting at least one portion of an edge, wherein the portion of the edge provides an indication that ringing artifact are probable; subjecting at least one portion of a pixel, related to the at least a portion of the edge, to a low pass filter to produce a filtered pixel; and blending the filtered pixel with a value relating to the filter prior to filtering to produce a filtered image.

Abstract: A motion estimation (ME) apparatus and method for approximating motion in a macroblock of an image. The ME method includes selecting at least one search center in the macroblock; searching for an adaptive density lattice, wherein the adaptive density lattice search results in a motion vector for the at least one selected search center; performing skip box search to refine the resulting motion vector; selecting a partition size for the macroblock utilizing the refined motion vector, resulting in a motion vector candidate; and performing a sub-pel refinement for the motion vector candidates.

Abstract: Preprocessing for motion-compensated video encoding such as MPEG includes lowpass filtering, temporal (310) and/or spatial (312), locally per pixel in response to motion vector analysis and prediction error (304) and temporal change (306). This de-emphasizes image areas of rapid change which corresponds to human perception de-emphasis.

Abstract: Preprocessing for motion-compensated video encoding such as MPEG includes lowpass filtering, temporal (310) and/or spatial (312), locally per pixel in response to motion vector analysis and prediction error (304) and temporal change (306). This de-emphasizes image areas of rapid change which corresponds to human perception de-emphasis.