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Parameter estimation to remove Gaussian/impulsive noise using a Kalman filter

机译:Parameter estimation to remove Gaussian/impulsive noise using a Kalman filter

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摘要

Recently, the lossless DCT (LDCT), which has the lifting structure and the rounding operations, is attracting many researchers' attention as an effective method for DCT based lossy/lossless unified coding. So far, previous reports regarding the LDCT focused to a few topics such as how to reduce the number of multipliers with the four point lossless Hadamard transform and the non-separable two dimensional LDCT. However, it is not analyzed enough how to express multiplier's word length as short as possible for attaining low computational load. This report, therefore, defines a new "image sensitivity" as an indicator of how the word length truncation of each coefficient affects quality of the decoded image. In addition, this report proposes a new word length allocation method based on the "image sensitivity". As a result, 2 bit in average shorter word length is attained maintaining decoded image quality compared to the case of using the same word length.

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