SMRT: A new placement approach of 2-D unique MRT coefficients for N a power of 2

Jaya, V.L.; Basu, Preetha; Gopikakumari, R.

doi:10.1109/indcon.2012.6420621

Cited by 5 publications

(3 citation statements)

References 3 publications

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“…Thus if the UMRT computation exploiting the sparsity of basis matrices proposed in this paper is used in frequency domain analysis of 2-D signals, especially for applications like video processing and image enhancement where size of the image taken is large, the computation time will be drastically reduced. An alternate placement approach for arranging the unique MRT coefficients in the order of sequencies is proposed in [11] named as SMRT. Since the basis matrices are the same, the proposed algorithm can be used to reduce the computational complexity of SMRT computation also.…”

Section: Resultsmentioning

confidence: 99%

Sparse Matrix based Computational Overhead Reduction in UMRT for N a power of 2

Basu¹,

Gopikakumari²

2013

IJCA

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Unique Mapped Real Transform (UMRT) is a transform which helps in frequency domain analysis of signals in the real domain. Different algorithms are developed for the computation of the unique MRT coefficients for N a power of 2 and for N an even number. They identify and place the UMRT coefficients in the form of an N N UMRT matrix.The basis matrices of this transform are observed to be sparse in nature. In this paper a new technique is proposed to reduce the computational overhead in UMRT, the size N being a power of two, exploiting the sparse nature of the basis matrices. General TermsFrequency domain analysis, Sparse representation.

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Section: Resultsmentioning

confidence: 99%

Sparse Matrix based Computational Overhead Reduction in UMRT for N a power of 2

Basu¹,

Gopikakumari²

2013

IJCA

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“…In [16] visual patterns of UMRT coefficients were analyzed and found that they have a specific pattern. These patterns when reordered results in a new pattern.…”

Section: B Smrtmentioning

confidence: 99%

“…If the reordering is done according to the number of sign changes, it results in a new visual pattern. Based on this a new placement scheme is derived in [16] terms of sequencies along columns and rows. This new scheme is termed as Sequency based MRT, SMRT.…”

Section: B Smrtmentioning

confidence: 99%

8 × 8 SMRT Based Texture Descriptors

Manju¹,

Jaya²,

Meenakshy³

et al. 2015

LNSE

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Abstract-In this paper texture features based on mapped real transform (MRT) is studied. Redundancy exists in MRT coefficients. Different algorithms have been proposed for removing the redundancy and placing the MRT coefficients. SMRT is a placement scheme based on sequency of the coefficients. The paper presents texture feature extraction based on SMRT placement algorithm. SMRT based texture feature extraction is found to be faster compared to UMRT based method.Index Terms-Texture descriptors, MRT, feature extraction.

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Sequency-based mapped real transform: properties and applications

Jaya¹,

Gopikakumari

2017

SIViP

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SMRT: A new placement approach of 2-D unique MRT coefficients for N a power of 2

Cited by 5 publications

References 3 publications

Sparse Matrix based Computational Overhead Reduction in UMRT for N a power of 2

Sparse Matrix based Computational Overhead Reduction in UMRT for N a power of 2

8 × 8 SMRT Based Texture Descriptors

Sequency-based mapped real transform: properties and applications

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