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文件名称:MSc---Orthogonal-vs-Biorthogonal-Wavelets-for-Ima
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E ective image compression requires a non-expansive discrete wavelet transform (DWT) be
employed consequently, image border extension is a critical issue. Ideally, the image border
extension method should not introduce distortion under compression. It has been shown in
literature that symmetric extension performs better than periodic extension. However, the
non-expansive, symmetric extension using fast Fourier transform and circular convolution
DWT methods require symmetric lters. This precludes orthogonal wavelets for image compression
since they cannot simultaneously possess the desirable properties of orthogonality
and symmetry. Thus, biorthogonal wavelets have been the de facto standard for image compression
applications. The viability of symmetric extension with biorthogonal wavelets is
the primary reason cited for their superior performance.-E ective image compression requires a non-expansive discrete wavelet transform (DWT) be
employed consequently, image border extension is a critical issue. Ideally, the image border
extension method should not introduce distortion under compression. It has been shown in
literature that symmetric extension performs better than periodic extension. However, the
non-expansive, symmetric extension using fast Fourier transform and circular convolution
DWT methods require symmetric lters. This precludes orthogonal wavelets for image compression
since they cannot simultaneously possess the desirable properties of orthogonality
and symmetry. Thus, biorthogonal wavelets have been the de facto standard for image compression
applications. The viability of symmetric extension with biorthogonal wavelets is
the primary reason cited for their superior performance.
employed consequently, image border extension is a critical issue. Ideally, the image border
extension method should not introduce distortion under compression. It has been shown in
literature that symmetric extension performs better than periodic extension. However, the
non-expansive, symmetric extension using fast Fourier transform and circular convolution
DWT methods require symmetric lters. This precludes orthogonal wavelets for image compression
since they cannot simultaneously possess the desirable properties of orthogonality
and symmetry. Thus, biorthogonal wavelets have been the de facto standard for image compression
applications. The viability of symmetric extension with biorthogonal wavelets is
the primary reason cited for their superior performance.-E ective image compression requires a non-expansive discrete wavelet transform (DWT) be
employed consequently, image border extension is a critical issue. Ideally, the image border
extension method should not introduce distortion under compression. It has been shown in
literature that symmetric extension performs better than periodic extension. However, the
non-expansive, symmetric extension using fast Fourier transform and circular convolution
DWT methods require symmetric lters. This precludes orthogonal wavelets for image compression
since they cannot simultaneously possess the desirable properties of orthogonality
and symmetry. Thus, biorthogonal wavelets have been the de facto standard for image compression
applications. The viability of symmetric extension with biorthogonal wavelets is
the primary reason cited for their superior performance.
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MSc - Orthogonal vs Biorthogonal Wavelets for Image compression.pdf
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