Design of orthogonal filterbanks with rational coefficients using Grobner bases

Design and implementation of a novel low complexity symmetric orthogonal wavelet filter‐bank

“…The values in Table 1 are obtained after first level wavelet decomposition of standard Baboon, Parrot, Lena and Barbara images. It is observed that the proposed FB preserves energy distribution when compared with existing FBs [9, 18, 33, 34].…”

“…Also, throughput is very less due to the over utilisation of huge internal computing units. Recently, Le et al [33] proposed an approach to design rational orthogonal wavelet FBs (db3) using Grobner basis. This basis is used to find better lattice parameters for rationalising db3 irrational filter coefficients.…”

“…The frequency responses of the proposed analysis LPF and HPF are compared with the same length original db3 [9] and recently published FBs [18, 33, 34] as shown in Fig. 5.…”

“…6. It is observed that the frequency response of the proposed FB gives less energy of error as compared to existing FBs [18, 33, 34].…”

“…It is known that energy distribution in the wavelet sub‐bands after decomposition decides the suitability of wavelet for any application [35]. Table 1 shows the comparison of the percentage energy distribution of the designed wavelet with original db3 [9] and existing wavelet FBs [18, 33, 34]. The values in Table 1 are obtained after first level wavelet decomposition of standard Baboon, Parrot, Lena and Barbara images.…”