Efficient encoding/decoding of a sequence of data frames
First Claim
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1. An encoder for encoding a sequence of data frames, said encoder comprising:
- a first transformation block receiving a first data frame contained in said sequence of data frames and generating a transformed frame according to a discrete cosine transformation approach;
a prediction block generating a predicted frame corresponding to said first data frame from data frames prior to said first data frame in said sequence using a prediction approach selected from a group consisting of a mean prediction, a horizontal prediction and a vertical prediction, wherein a reduced number of data values for each micro block of the data frames prior to said first data frame is computed;
a second transformation block generating a transformed predicted data by processing said predicted frame also according to said discrete cosine transformation approach;
a subtractor block generating a difference of said transformed predicted data and said transformed frame to generate a difference data; and
a quantization block quantizing said difference data to generate quantized data corresponding to said first data frame.
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Abstract
Encoding data by first performing a transformation of predicted data and input data, and then performing a subtraction of the resulting outputs. In an embodiment, the prediction approach is chosen such that fewer elements of different values (compared to a number of elements in the input data) are generated, and the different values are generated in a predictable position. The transformation approach is chosen such that the output expressly represents variations in the input data as well as satisfies a distributive property. The decoding may be performed based on the same concepts. As a result, the data can be encoded and/or decoded efficiently.
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Citations
20 Claims
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1. An encoder for encoding a sequence of data frames, said encoder comprising:
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a first transformation block receiving a first data frame contained in said sequence of data frames and generating a transformed frame according to a discrete cosine transformation approach; a prediction block generating a predicted frame corresponding to said first data frame from data frames prior to said first data frame in said sequence using a prediction approach selected from a group consisting of a mean prediction, a horizontal prediction and a vertical prediction, wherein a reduced number of data values for each micro block of the data frames prior to said first data frame is computed; a second transformation block generating a transformed predicted data by processing said predicted frame also according to said discrete cosine transformation approach; a subtractor block generating a difference of said transformed predicted data and said transformed frame to generate a difference data; and a quantization block quantizing said difference data to generate quantized data corresponding to said first data frame. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A decoder for decoding a sequence of encoded data frames, said decoder comprising:
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an inverse quantization block generating a plurality of scaled values corresponding to the digital values in a first encoded data frame contained in said sequence of encoded data frames; a prediction block generating a predicted frame corresponding to said first encoded data frame from data frames prior to said first encoded data frame in said sequence using a prediction approach selected from the group consisting of a mean prediction, a horizontal prediction, a vertical prediction, wherein a reduced number of data values for each micro block of the data frames prior to said first encoded data is computed; a transformation block transforming said predicted frame according to a discrete cosine transformation approach to generate a transformed frame; an adder adding respective values of said transformed frame and said plurality of scaled values to generate an added frame; and a first inverse transformation block performing an inverse transform of said discrete cosine transformation approach on said added frame to generate a decoded frame corresponding to said first encoded data frame. - View Dependent Claims (8, 9, 10, 11)
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12. A method of processing a plurality of data frames, said method comprising:
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receiving a first data frame contained in a sequence of data frames and generating a transformed frame according to a discrete cosine transformation approach, wherein said sequence of data frames are contained in said plurality of data frames; generating a predicted frame corresponding to said first data frame from data frames prior to said first data frame in said sequence using a prediction approach selected from a group consisting of a mean prediction, a horizontal prediction and a vertical prediction, wherein a reduced number of data values for each micro block of the data frames prior to said first data frame is computed; generating a transformed predicted data by processing said predicted frame also according to said discrete cosine transformation approach; generating a difference of said transformed predicted data and said transformed frame to generate a difference data; and quantizing said difference data to generate quantized data corresponding to said first data frame. - View Dependent Claims (13, 14, 15, 16)
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17. A non-transitory machine readable medium carrying one or more sequences of instructions for causing a system to process a plurality of data frames, wherein execution of said one or more sequences of instructions by one or more processors contained in said system causes said system to perform the actions of:
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receiving a first data frame contained in a sequence of data frames and generating a transformed frame according to a discrete cosine transformation approach, wherein said sequence of data frames are contained in said plurality of data frames; generating a predicted frame corresponding to said first data frame from data frames prior to said first data frame in said sequence using a prediction approach, wherein a reduced number of data values for each micro block of the data frames prior to said first data frame is computed; generating a transformed predicted data by processing said predicted frame also according to said discrete cosine transformation approach; generating a difference of said transformed predicted data and said transformed frame to generate a difference data; and quantizing said difference data to generate quantized data corresponding to said first data frame. - View Dependent Claims (18, 19, 20)
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Specification