A filter design technique for steerable pyramid image transforms

Karasaridis, Anestis; Simoncelli, Eero P.

doi:10.1109/icassp.1996.547763

Cited by 58 publications

(41 citation statements)

References 6 publications

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“…This description provides information about the image contained in time-frequency domain, and thus provides a powerful tool for the description of similar textures. Several multiresolution and multichannel transform algorithms have been used for texture classification, such as the dyadic wavelet transform (Arivazhagan and Ganesan, 2003, wavelet frame transform (Unser, 1995), Gabor filters Farrokhnia, 1991, Manjunath andMa, 1996) and the steerable pyramid Freeman, 1995, Karasaridis andSimoncelli, 1996).…”

Section: Introductionmentioning

confidence: 99%

Comparison and fusion of multiresolution features for texture classification

Shawe‐Taylor

2005

Pattern Recognition Letters

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In this paper, we investigate the texture classification problem with individual and combined multiresolution features, i.e., dyadic wavelet, wavelet frame, Gabor wavelet, and steerable pyramid. Support vector machines are used as classifiers. The experimental results show that the steerable pyramid and Gabor wavelet classify texture images with the highest accuracy, the wavelet frame follows them, the dyadic wavelet significantly lags behind.Experimental results on fused features demonstrated the combination of two feature sets always outperformed each method individually. And the fused feature sets of multi-orientation decompositions and stationary wavelet achieve the highest accuracy.

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Section: Introductionmentioning

confidence: 99%

Comparison and fusion of multiresolution features for texture classification

Shawe‐Taylor

2005

Pattern Recognition Letters

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“…In order to achieve some degree of rotation invariance, some methods use averages of the three bands to achieve fea- Simoncelli et al [35,72] developed steerable pyramids, a redundant frame representation which is rotation and translation invariant, but which is data intensive.…”

Section: Invariance; Review Of Previous Workmentioning

confidence: 99%

Three-dimensional object registration using wavelet features

Chalfant

Patrikalakis

2009

Engineering with Computers

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Recent developments in shape-based modeling and data acquisition have brought three-dimensional models to the forefront of computer graphics and visualization research. New data acquisition methods are producing large numbers of models in a variety of fields. Three-dimensional shape-based matching and registration (alignment) are key to the useful application of such models in areas from automated surface inspection to cancer detection and surgery. The three-dimensional models in these applications are typically huge. State-of-the-art simulations in computational fluid dynamics produce upward of four terabytes of data per second of flow. Research-level magnetic resonance imaging (MRI) resolutions can reach 1 cubic micro-meter. As a result, object registration and matching algorithms must handle very large amounts of data.The algorithms developed in this thesis accomplish automatic registration and matching of three-dimensional voxelized models. We employ features in a wavelet transform domain to accomplish registration. The features are extracted in a multiresolutional format, thus delineating features at various scales for robust and rapid matching. Registration is achieved through seeking peaks in sets of rotation quaternions using a voting scheme, then separately identifying translation. The method is robust to occlusion, clutter and noise. The efficacy of the algorithm is demonstrated through examples from solid modeling and medical imaging applications.

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“…Illustration of SPT [7] : Recursively insert the sub-system in the dashed box at the location of the filled circle results in a multi-layer pyramid transform. [18] ，文献 [7]设计的 SPT 滤波…”

Section: 引言mentioning

confidence: 99%

基于SVD方法设计几何变形可控的金字塔变换<br>Design Deformable Pyramid Transform via SVD Approach

春桃¹

2013

CSA

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This paper presents a deformable pyramid transform (DPT) with shift-invariance, steerability, and scalability. This DPT is extended from a numerical steerable pyramid transform (SPT). We take each steerable basis filter of the SPT as the kernel. For each kernel, we employ the singular value decomposition (SVD) approach to construct scalable basis filters and their corresponding interpolation functions. These scalable basis filters are used as analysis filters of the DPT. Its synthesis filters are then theoretically derived under the constraint of perfect reconstruction for analysis and synthesis filters. In addition, we theoretically derive the interpolation function for steerability, and quantitatively analyze the relationship between the number of scalable basis filters and the reconstruction performance. Numerical simulations demonstrate that the proposed scalable basis filters satisfy the constraint of perfect reconstruction. Also, it is observed that merely using half of the number of scalable basis filters can approximate the optimum reconstruction performance at a cost of reconstruction error within 1 dB. Keywords:

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A filter design technique for steerable pyramid image transforms

Cited by 58 publications

References 6 publications

Comparison and fusion of multiresolution features for texture classification

Comparison and fusion of multiresolution features for texture classification

Three-dimensional object registration using wavelet features

基于SVD方法设计几何变形可控的金字塔变换<br>Design Deformable Pyramid Transform via SVD Approach

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