Quantization errors and errors due to finite word-length registers in processors result in undesirable responses in many cases. Along with these two errors, in some cases, data samples may not have exact representations in binary form. Hence it is very important to mitigate the effects of these errors. In this paper, we discuss the various errors arising in digital filters and the effect of using integer sequences for windowing techniques in FIR filtering to minimize these errors. We find that using integer sequences as window functions, the error in filter coefficients reduce by at least 30% in case of lower magnitude coefficients .
In this paper a data hiding method based on pixel pair matching (PPM) is presented. Pixel pair matching uses a pair of pixel intensity values as reference coordinates and searches the coordinate neighborhood according to the given message digit. The searched coordinate which encodes the message digit is put in place of the pixel pair. Exploiting modification direction (EMD), Diamond Encoding (DE) and Adaptive Pixel Pair Matching (APPM) are recently proposed methods based on PPM. Among these Adaptive Pixel Pair Matching provides the highest capacity of embedding with a given distortion. This paper presents an extension of the method to higher dimensional coordinate system and in particular with Pixel Triplet Matching (PTM). The experiments showed that PTM achieves higher capacity while being computationally feasible. The method is also resistant to simple steganalysis with adjacent HCF-COM.
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