Texas Instruments Corporation

Fan Zhai

Weider Peter Chang

Karl H Renner

Ramesh Chandrasekaran

Hsindao E Lu

A content-adaptive edge and detail enhancement apparatus is described for image/video processing. Both 2D peaking and LTI/CTI are used in sharpening pictures. Image analysis is performed to generate a blending factor to control the use of the two peaking techniques. The strength or likelihood of edges or transitions is measured and such a strength or likelihood measurement will be transformed into the blending factor controlling the blending of the LTI/CTI and peaking outputs.

Content adaptive edge and detail enhancement for image and video processing

A content-adaptive edge and detail enhancement method is described for image/video processing. Both 2D peaking and LTI/CTI are used in sharpening pictures. Image analysis is performed to generate a mask to control the use of the two peaking techniques. The strength or likelihood of edges or transitions is measured and such a strength or likelihood measurement will be transformed into a blending factor controlling the blending of the LTI/CTI and peaking outputs.

Film mode detection with bad edit detection used in de-interlacing video includes use of combing artifact detection in both 3-2 pull down detection and 2-2 pull down detection. Further, combing artifact detection uses only two field memories by accumulation of partial field statistics for comparisons.

Film mode detection

A method for motion detection is provided that includes determining a first motion measure for a pixel based on differences between first neighboring pixels of the pixel, determining a detail measure for the pixel, wherein the detail measure is indicative of an amount of detail in second neighboring pixels of the pixel, adapting a first coring threshold and a first gain of a first transfer function based on the detail measure, and using the adapted first transfer function to map the first motion measure to a first motion parameter.

Motion detection in video with large areas of detail

Motion detection in interlaced video fields, as useful in de-interlacing, includes spatial-temporal maximum filtering, temporal IIR filtering dependent upon spatial-temporal variance, and spatial variance dependent moving-still interpolation blending factor.

Motion detection for interlaced video

An edge direction vector determination, which can be used for video interlaced-to-progressive conversion by motion-adaptive interpolation, has a coarse edge vector determination over a large search window followed by a fine edge vector determination over a small window plus confidence level assessment for field interpolation.

Interlaced-to-progressive video processing

A method and apparatus for ringing artifacts reduction for compressed video signals. The method includes receiving luma data to the digital signal processor, calculating sum of gradient of the luma data; calculating SAD of the luma data; performing pixel classification based of the calculated SAD and sum of gradient, performing erosion on a detected edge pixel indicator on a detected flat pixel indicators, determining at least one of the strength or weakness of the an edge based on the determined edge erosion, performing horizontal dilation on the detected edge pixel indicators and edge strength; and performing at least one of sigma or bilateral filtering to the luma data according to the detected edge pixel indicator, flat pixel indicator, edge strength, the number of very flat pixel in the block.

Method and apparatus for reducing ringing artifacts

In one embodiment, a method for processing a video signal includes: (1) receiving and storing luminance and chrominance information for each pixel in a first portion of the signal; (2) receiving luminance and chrominance information for each pixel in a second portion of the signal; (3) determining an estimated motion vector for each particular pixel of the second portion by comparing the luminance and chrominance information of the particular pixel to the stored luminance and chrominance information for one or more pixels in a search area of the first portion to determine a pixel in the search area that most closely matches the particular pixel and determining the estimated motion vector according to the particular pixel and the most closely matching pixel; (4) using the estimated motion vector to access the chrominance information for the most closely matching pixel; (5) using a three-dimensional comb filter to filter the chrominance information for the particular pixel and for the most closely matching pixel to determine three-dimensional filter output chrominance information for the particular pixel; (6) receiving the three-dimensional output chrominance information and if the chrominance information for the particular pixel matches the chrominance information of the most closely matching pixel within a specified tolerance, using the three-dimensional filter output chrominance information to determine output luminance information for the particular pixel; and (7) providing the three-dimensional output chrominance information and output luminance information for the particular pixel for displaying the particular pixel.

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Richardson, TX, United States of America

Fan Zhai