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Proportional Convolution Filters - An Alternative Technique For Non-distorted Image Enhancement
Authors
Branco F.C.
de Almeida T.I.R.
Filho C.R.S.
Publication date
26 November 2015
Publisher
Abstract
This paper introduces a new class of spatial filters, here coined the proportional convolution filters. These filters are constructed in such way that the values assigned to each kernel cell are weighted as a function of the trigonometric distance of the cells to the kernel centre. A set of high-pass and low-pass proportional filters were designed using a specially tailored algorithm and a Delphi-based code that allows producing multi-dimensional filters. These filters underwent a twofold test. Firstly, the filters were tested against an instructive digital image of a candle flame. This image was employed as it shows large and detailed variations in color tones (low frequencies) and an assortment of possible boundaries between tones (high frequencies). Secondly, the filters were applied to a Landsat-5 TM image containing a variety of landforms. Results showed the efficiency of the filters and the adequacy of an array of kernel sizes to enhance both tonal and edge variations in a digital image, demonstrating that the proportional filters can benefit numerous applications in several fields of Geosciences. © 2012 Sociedade Brasileira de Geofísica.3013139Blom, R.G., Daily, M., Radar Image-Processing for Rock-Type Discrimination (1982) IEEE Transactions On Geoscience and Remote Sensing, 20 (3), pp. 343-351Branco, F.C., (1998) Filtros De Convolução Passa Baixas No Realce Tonal De Imagens, p. 78. , M.Sc. Dissertation. Instituto de Geociências - USP. São Paulo, SP, BrazilCurran, P.J., (1985) Principles of Remote Sensing, p. 282. , Longman Group Limited, London, UKDrury, S.A., (2001) Image Interpretation In Geology, p. 296. , Blackwell Science, UK, 3rd editionHoldermann, F., Bohner, M., Bargel, B., Kazmierczak, H., Review of Automatic Image Processing (1978) Photogrammetria, 34, pp. 225-258Mather, P.M., (1999) Computer Processing of Remotely-Sensed Images: An Introduction, p. 292. , John Wiley & Sons Inc., UKSouza, F.C.R., Drury, S.A., Denniss, A.M., Carlton, R.W.T., Rothery, D.A., Restoration of Corrupted Optical Fuyo-1 (JERS-1) Data Using Frequency Domain Techniques (1996) Photogrammetric Engineering & Remote Sensing, 62 (9), pp. 1037-1047Tao, L., Asari, V., An Integrated Neighborhood Dependent Approach for Nonlinear Enhancement of Color Images (2004) International Conference On Information Technology, Proceedings, 2, pp. 138-13
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Last time updated on 10/04/2020