Cisco Technology, Inc.

Tandberg Telecom As

Steinar Midtskogen

Arild Fuldseth

Tom-Ivar Johansen

Lars Petter Endresen

Stian Selnes

Andreas Kaljord

A target sample x(i,j) of a two-dimensional array of reconstructed samples is filtered based on values of samples in a neighboring region of the target sample to produce a two-dimensional array of modified reconstructed samples, according to the equation: y(i,j)=round(x(i,j)+g(&#x3a3;a(m,n)&#x192;(x(i,j)&#x2212;b(m,n)&#xd7;(m,n)))), where y(i,j) is a modified target sample value, R is the neighboring region of the target sample, a(m,n) and b(m,n) are real-valued coefficients, round(x) is a function that maps the value x to an integer value in the range [0,2&#x2212;1], B is the number of bits representing each sample of the two-dimensional array of modified reconstructed samples, f(x) and g(x) are functions, wherein (a) f(x) is a non-linear function, or (b) g(x) is a non-linear function and both a width and a height of R is more than one sample.

Generalized filter for removing video compression artifacts

Presented herein are techniques for filtering pixels during video coding and decoding operations. Similar operations are performed at a video encoder and a video decoder. For a target pixel in a block of a video frame represented by the encoded bit-stream, a value of the target pixel is compared with neighboring pixels to produce a plurality of comparison results. A particular offset value for the target pixel is derived based on the plurality of comparison results. The target pixel is filtered using the particular offset value. This process is performed for some or all of the pixels of blocks of a video frame.

Efficient loop filter for video codec

A target sample x(i,j) of a two-dimensional array of reconstructed samples is filtered based on values of samples in a neighboring region of the target sample to produce a two-dimensional array of modified reconstructed samples, according to the equation: y(i,j)=round(x(i,j)+g(&#x3a3;a(m,n)&#x192;(x(i,j)&#x2212;b(m,n)x(m,n)))), where y(i,j) is a modified target sample value, R is the neighboring region of the target sample, a(m,n) and b(m,n) are real-valued coefficients, round(x) is a function that maps the value x to an integer value in the range [0,2&#x2212;1], B is the number of bits representing each sample of the two-dimensional array of modified reconstructed samples, &#x192;(x) and g(x) are functions, wherein (a) &#x192;(x) is a non-linear function, or (b) g(x) is a non-linear function and both a width and a height of R is more than one sample.

A target sample x(i,j) of a two-dimensional array of reconstructed samples is filtered based on values of samples in a neighboring region of the target sample to produce a two-dimensional array of modified reconstructed samples, according to the equation: y(i,j)=round (x(i, j)+g(&#x3a3;a(m, n)f(x(i,j)&#x2212;b(m,n)x(m,n)))), where y(i,j) is a modified target sample value, R is the neighboring region of the target sample, a(m,n) and b(m,n) are real-valued coefficients, round(x) is a function that maps the value x to an integer value in the range [0,2-1], B is the number of bits representing each sample of the two-dimensional array of modified reconstructed samples, f(x) and g(x) are functions, wherein (a) f(x) is a non-linear function, or (b) g(x) is a non-linear function and both a width and a height of R is more than one sample.

A video processing system, method and computer program storage device cooperate to provide a resource and performance efficient sub-pixel motion search operation. Using on the fly calculations it is possible to provide approximations of sub-pixel positions on one image with respect to another image in an image sequence. A sub-pixel position used to set a motion vector for an encoding process may then be identified with reduced processing and memory resources relative to conventional techniques. Also, by later performing a full encoding cost analysis on the earlier identified sub-pixel position, and keeping track of differences, an interpolation accuracy may be dynamically improved by applying the differences to subsequent image frames.

Method, apparatus and computer program product for image motion prediction

A system, apparatus, method, and computer program product for detecting and correcting packet losses that adversely affect video quality. This packet loss feature may be employed as part of the secure video conference system, method and computer program product, or be employed in a non-secure system, method and computer program product.

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Oslo, Norway

Steinar Midtskogen