Correlation postprocessing-based method for the detection of defocused images

Carnicer, Artur; Vallmitjana, Santiago; Juvells, Ignasi

doi:10.1364/ao.36.004807

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…The classical matched spatial filter (MSF) 1 is often not adequate for practical pattern recognition since its performance degrades rapidly when the reference object is distorted. Therefore, many improvements in correlation filters in the frequency domain [2][3][4][5] , and pre- [6][7][8] and post- [9][10][11] processing techniques in the spatial domain have been explored. Most of them involve the design of filters tolerable to various distortions such as noise, scale change, rotation and illumination.…”

Section: Introductionmentioning

confidence: 99%

<title>Standards-compatible compression for automated image recognition in sensor networks and surveillance systems</title>

2004

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We show that the standard image compression algorithms are not suitable for compressing images in correlation pattern recognition since they aim at retaining image fidelity in terms of perceptual quality rather than preserving spectrally significant information for pattern recognition. New compression algorithms for pattern recognition are therefore developed, which are based on the modification of the standard compression algorithms to achieve higher compression ratio and simultaneously to enhance pattern recognition performance. This is done by emphasizing middle and high frequency components and discarding low frequency components according to a new developed distortion measure for compression. The operations of denoising, edge enhancement and compression can be integrated in the encoding process in the proposed compression algorithms. Simulation results show the effectiveness of the proposed compression algorithms.

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Section: Introductionmentioning

confidence: 99%

<title>Standards-compatible compression for automated image recognition in sensor networks and surveillance systems</title>

2004

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“…The classical matched spatial filter ͑MSF͒ 1 is often not adequate for practical pattern recognition, since its performance degrades rapidly when the reference object is distorted. Therefore, many improved correlation filters in the frequency domain 2-5 and pre- [6][7][8] and postprocessing [9][10][11] techniques in the spatial domain have been explored. Most of them involve the design of filters tolerating various distortions such as noise, scale change, rotation, and illumination.…”

Section: Introductionmentioning

confidence: 99%

Modification of standard image compression methods for correlation-based pattern recognition

2004

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Standard image compression algorithms may not perform well in compressing images for pattern recognition applications, since they aim at retaining image fidelity in terms of perceptual quality rather than preserving spectrally significant information for pattern recognition. New compression algorithms for pattern recognition are therefore investigated, which are based on the modification of the standard compression algorithms to simultaneously achieve higher compression ratio and improved pattern recognition performance. This is done by emphasizing middle and high frequencies and discarding low frequencies according to a new distortion measure for compression. The operations of denoising, edge enhancement, and compression can be integrated in the same encoding process in the proposed compression algorithms. Simulation results show the effectiveness of the proposed compression algorithms.

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Morphologically preprocessed joint transform correlation

Zhang

Karim

1999

Appl. Opt.

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A morphologically preprocessed joint transform correlation is proposed that combines the techniques of morphological filtering and joint transform correlation. We improve on the performance of a joint transform correlator by eliminating noise with morphological preprocessing and by performing edge detection of input images. Computer simulation results show that the corresponding system contributes to a better discrimination capability than gradient operator-based and wavelet-based preprocessed joint transform correlation.

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Correlation postprocessing-based method for the detection of defocused images

Cited by 3 publications

References 9 publications

<title>Standards-compatible compression for automated image recognition in sensor networks and surveillance systems</title>

<title>Standards-compatible compression for automated image recognition in sensor networks and surveillance systems</title>

Modification of standard image compression methods for correlation-based pattern recognition

Morphologically preprocessed joint transform correlation

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