Quantification of Finite Word Length Effects in Filter Banks and Wavelet Transform

G. Snehal, Dr. T. Srikanth
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Abstract

It is known that computers store numbers not with infinite precision but rather in some approximation that can be packed into a fixed number of bits, and this leads to loss of information. Present work studies the effect of loss of information on the response of filter banks and Wavelet transform. These effects are universally called Finite word length effects. There are number of effects of finite word length like overflow and truncation errors in addition, and multiplication, effects of coefficient quantization, limit cycle, etc. Present focus is on coefficient quantization. To see Finite word length effects in filter banks and Wavelet transform authors have used algorithm in which image has been first wavelet transformed and again constructed back using quantized coefficients. Pyramidal algorithm with DAUB4 wavelet has been used. Simulation for both direct quantization of DAUB4 coefficients and equivalent lattice coefficients quantization has been performed. All simulations are done in C.
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滤波器组有限字长效应的量化与小波变换
众所周知,计算机存储的数字不是无限精确的,而是某种近似的,可以打包成固定的位数,这就导致了信息的丢失。本文研究了信息丢失对滤波器组和小波变换响应的影响。这些效应通常被称为有限字长效应。有限字长的影响有很多,比如溢出和截断错误,以及乘法、系数量化、极限环等影响。目前的重点是系数量化。为了了解滤波器组和小波变换中的有限字长效应,作者使用了一种算法,该算法首先对图像进行小波变换,然后再使用量化系数进行构造。采用了DAUB4小波的锥体算法。对DAUB4系数的直接量化和等效晶格系数的量化进行了仿真。所有的模拟都是用C语言完成的。
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