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It is set to the average of the motion estimations of the three neighbours with the lowest SAD. After estimation at the lowest (256 x 256 ) level, the vector estimations are compared with the difference picture which represents the pixel differences between the motion uncompensated previous image frame and the current one. At those locations, where the difference is less than a certain threshold, the motion vector is set to zero. This reduces the errors that have been accumulated from one level to the next level.

Therefore, noise removal operations on only one channel are not adequate and a multichannel filter is necessary to remove the noise and restore the originally transmitted signal. 2. A M U L T I C H A N N E L F I L T E R F O R I M P U L S I V E N O I S E R E D U C T I O N Impulsive noise can be classified as a short duration high energy spike, which results in the alteration of the digital value of the image pixel. After the effect of the noise, the altered value of the image pixel usually differs from the corresponding values of the neighboring pixels.

Digitizing this kind of film material results in images having patches with gray level values that are uncorrelated to the pixel neighborhood. To avoid a distortion of the unaffected parts of the image, first the locations of the blotches and scratches have to be detected before the restoration algorithm can be applied. These locations are especially characterized by a discontinuity in the sequence. In this paper we present an algorithm that works much more effectively and with less computational load than other known algorithms [ 1].

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