Filter banks allowing perfect reconstruction
Signal Processing
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ten lectures on wavelets
Multirate systems and filter banks
Multirate systems and filter banks
Wavelets and subband coding
Multirate Digital Signal Processing
Multirate Digital Signal Processing
Multirate Digital Signal Processing: Multirate Systems, Filter Banks, Wavelets
Multirate Digital Signal Processing: Multirate Systems, Filter Banks, Wavelets
Multiresolution Signal Decomposition: Transforms, Subbands, and Wavelets
Multiresolution Signal Decomposition: Transforms, Subbands, and Wavelets
Wavelet filter evaluation for image compression
IEEE Transactions on Image Processing
Digital Signal Processing
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A new generalized way of signal decomposition and reconstruction entitled ISITRA is proposed. It is similar to the 2-channel filter bank scheme. In ISITRA, all the filters are obtained from a real vector. ISITRA allows decomposition of a signal into (1) an approximation and a detail, (2) two details and (3) two approximations. The latter two cases are not generally possible in the filter bank scheme. The choice of filter coefficients in ISITRA is much simpler and more arbitrary compared to that in the existing schemes. This allows one to find better filter coefficients for different applications. One can straight achieve an image compression ratio of 8:1 without doing any coding by modifying the range of pixel values in the decomposed components. One can also find a better set of decomposition and reconstruction filters than the commonly used Daubechies' wavelet filters of length 4. ISITRA is simpler and computationally marginally better than even the computationally efficient polyphase filter bank scheme.