Image analysis – Image compression or coding – Pyramid – hierarchy – or tree structure
Reexamination Certificate
2005-02-01
2005-02-01
Tran, Phuoc (Department: 2621)
Image analysis
Image compression or coding
Pyramid, hierarchy, or tree structure
C382S233000, C382S245000, C382S248000
Reexamination Certificate
active
06850649
ABSTRACT:
An encoder reorders quantized wavelet coefficients to cluster large and small wavelet coefficients into separate groups without requiring the use of data-dependent data structures. The coefficients are then adaptively encoded based on a run-length code which continuously modifies a parameter that controls the codewords uses to represent strings of quantized coefficients, seeking to minimize the number of bits spent in the codewords. A matrix of indices contains the coarsest coefficients in the upper left corner, and filling in low high and high low sub bands in larger and larger blocks in an alternating manner, such that low high sub bands comprise the top of the matrix and the high low sub bands comprise the left side of the matrix. The shortest codewords are assigned to represent a run of the most likely character having length of 2k, where k is a parameter. k is adjusted based on successive characters being encountered. k is increased when the character is the same, and decreased when the character is different. A decoder applies the above in reverse order. Decoding of the encoded coefficients is first performed, followed by an unshuffling of the coefficients. The unshuffled coefficients are then subjected to an inverse wavelet transform to recover the transformed and compressed data, such as image pixels.
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Lyon Richard T.
Lyon & Harr LLP
Microsoft Corporation
Tran Phuoc
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