Pixel Color Clustering of Multi-Temporally Acquired Digital Photographs of a Rice Canopy by Luminosity-Normalization and Pseudo-Red-Green-Blue Color Imaging
Red-green-blue (RGB) channels of RGB digital photographs were loaded with luminosity-adjusted R, G, and completely white grayscale images, respectively (RGwhtB method), or R, G, and R + G (RGB yellow) grayscale images, respectively (RGrgbyB method), to adjust the brightness of the entire area of mul...
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/450374 |
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| author | Ryoichi Doi Chusnul Arif Budi Indra Setiawan Masaru Mizoguchi |
| author_facet | Ryoichi Doi Chusnul Arif Budi Indra Setiawan Masaru Mizoguchi |
| author_sort | Ryoichi Doi |
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| description | Red-green-blue (RGB) channels of RGB digital photographs were loaded with luminosity-adjusted R, G, and completely white grayscale images, respectively (RGwhtB method), or R, G, and R + G (RGB yellow) grayscale images, respectively (RGrgbyB method), to adjust the brightness of the entire area of multi-temporally acquired color digital photographs of a rice canopy. From the RGwhtB or RGrgbyB pseudocolor image, cyan, magenta, CMYK yellow, black, L*, a*, and b* grayscale images were prepared. Using these grayscale images and R, G, and RGB yellow grayscale images, the luminosity-adjusted pixels of the canopy photographs were statistically clustered. With the RGrgbyB and the RGwhtB methods, seven and five major color clusters were given, respectively. The RGrgbyB method showed clear differences among three rice growth stages, and the vegetative stage was further divided into two substages. The RGwhtB method could not clearly discriminate between the second vegetative and midseason stages. The relative advantages of the RGrgbyB method were attributed to the R, G, B, magenta, yellow, L*, and a* grayscale images that contained richer information to show the colorimetrical differences among objects than those of the RGwhtB method. The comparison of rice canopy colors at different time points was enabled by the pseudocolor imaging method. |
| format | Article |
| id | doaj-art-49c42b9164a5415eb59aaa929b63c46b |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-49c42b9164a5415eb59aaa929b63c46b2025-02-03T06:06:57ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/450374450374Pixel Color Clustering of Multi-Temporally Acquired Digital Photographs of a Rice Canopy by Luminosity-Normalization and Pseudo-Red-Green-Blue Color ImagingRyoichi Doi0Chusnul Arif1Budi Indra Setiawan2Masaru Mizoguchi3Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, JapanGraduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, JapanDepartment of Civil and Environmental Engineering, Bogor Agricultural University, Kampus IPB Darmaga, Bogor 16680, IndonesiaGraduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, JapanRed-green-blue (RGB) channels of RGB digital photographs were loaded with luminosity-adjusted R, G, and completely white grayscale images, respectively (RGwhtB method), or R, G, and R + G (RGB yellow) grayscale images, respectively (RGrgbyB method), to adjust the brightness of the entire area of multi-temporally acquired color digital photographs of a rice canopy. From the RGwhtB or RGrgbyB pseudocolor image, cyan, magenta, CMYK yellow, black, L*, a*, and b* grayscale images were prepared. Using these grayscale images and R, G, and RGB yellow grayscale images, the luminosity-adjusted pixels of the canopy photographs were statistically clustered. With the RGrgbyB and the RGwhtB methods, seven and five major color clusters were given, respectively. The RGrgbyB method showed clear differences among three rice growth stages, and the vegetative stage was further divided into two substages. The RGwhtB method could not clearly discriminate between the second vegetative and midseason stages. The relative advantages of the RGrgbyB method were attributed to the R, G, B, magenta, yellow, L*, and a* grayscale images that contained richer information to show the colorimetrical differences among objects than those of the RGwhtB method. The comparison of rice canopy colors at different time points was enabled by the pseudocolor imaging method.http://dx.doi.org/10.1155/2014/450374 |
| spellingShingle | Ryoichi Doi Chusnul Arif Budi Indra Setiawan Masaru Mizoguchi Pixel Color Clustering of Multi-Temporally Acquired Digital Photographs of a Rice Canopy by Luminosity-Normalization and Pseudo-Red-Green-Blue Color Imaging The Scientific World Journal |
| title | Pixel Color Clustering of Multi-Temporally Acquired Digital Photographs of a Rice Canopy by Luminosity-Normalization and Pseudo-Red-Green-Blue Color Imaging |
| title_full | Pixel Color Clustering of Multi-Temporally Acquired Digital Photographs of a Rice Canopy by Luminosity-Normalization and Pseudo-Red-Green-Blue Color Imaging |
| title_fullStr | Pixel Color Clustering of Multi-Temporally Acquired Digital Photographs of a Rice Canopy by Luminosity-Normalization and Pseudo-Red-Green-Blue Color Imaging |
| title_full_unstemmed | Pixel Color Clustering of Multi-Temporally Acquired Digital Photographs of a Rice Canopy by Luminosity-Normalization and Pseudo-Red-Green-Blue Color Imaging |
| title_short | Pixel Color Clustering of Multi-Temporally Acquired Digital Photographs of a Rice Canopy by Luminosity-Normalization and Pseudo-Red-Green-Blue Color Imaging |
| title_sort | pixel color clustering of multi temporally acquired digital photographs of a rice canopy by luminosity normalization and pseudo red green blue color imaging |
| url | http://dx.doi.org/10.1155/2014/450374 |
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