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An efficient and self-adapted approach to the sharpening of color images.

Kau LJ, Lee TL - ScientificWorldJournal (2013)

Bottom Line: With the proposed approach, the discontinuities can be highlighted while most of the original information contained in the image can be retained.Finally, the adjusted channel of Value and that of Hue and Saturation will be integrated to get the sharpened color image.Extensive experiments on natural images will be given in this paper to highlight the effectiveness and efficiency of the proposed approach.

View Article: PubMed Central - PubMed

Affiliation: Department of Electronic Engineering & Graduate Institute of Computer and Communication Engineering, National Taipei University of Technology, No. 1 Section 3, Chung-Hsiao E. Road, Taipei 10608, Taiwan.

ABSTRACT
An efficient approach to the sharpening of color images is proposed in this paper. For this, the image to be sharpened is first transformed to the HSV color model, and then only the channel of Value will be used for the process of sharpening while the other channels are left unchanged. We then apply a proposed edge detector and low-pass filter to the channel of Value to pick out pixels around boundaries. After that, those pixels detected as around edges or boundaries are adjusted so that the boundary can be sharpened, and those nonedge pixels are kept unaltered. The increment or decrement magnitude that is to be added to those edge pixels is determined in an adaptive manner based on global statistics of the image and local statistics of the pixel to be sharpened. With the proposed approach, the discontinuities can be highlighted while most of the original information contained in the image can be retained. Finally, the adjusted channel of Value and that of Hue and Saturation will be integrated to get the sharpened color image. Extensive experiments on natural images will be given in this paper to highlight the effectiveness and efficiency of the proposed approach.

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Related in: MedlinePlus

θeth = 22 for HVD. (a) The image “Peppers” (512 × 512 color image). (b) Edges detected by HVD with LPF. (c and d) Sharpened results by HVD with scaling factors 0.5 and 1.0, respectively.
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fig7: θeth = 22 for HVD. (a) The image “Peppers” (512 × 512 color image). (b) Edges detected by HVD with LPF. (c and d) Sharpened results by HVD with scaling factors 0.5 and 1.0, respectively.

Mentions: In addition, we also show from Figures 6to 13 the sharpened results obtained by using the proposed approach to eight other color test images. As can be seen in Figures 6(c) and 6(d), the contour of the plane, the text on the plane, the pilot, and the mountain all have a very good visual quality when compared with the original image in Figure 6(a). For the test image “Peppers” in Figure 7, we can see in Figures 7(c) and 7(d) a very distinct contour around peppers and around the stalk of these peppers after the sharpening process when compared with the original image in Figure 7(a). For the test image “Woodland Hills, CA”, an aerial image, in Figure 8, we can see that the contour of the mountain, lake, roads and buildings are quite distinct in Figures 8(c) and 8(d) after the proposed sharpening process. Figure 9 shows the results of the well-known test image “Lena”. As can be seen in Figures 9(c) and 9(d), the contour around her eyes and the contour of the hair have become very conspicuous after the sharpening process. Figure 10 shows the results of the test image “Sailboat on lake”. When compared with the original image in Figure 10(a), a more conspicuous contour can be obtained for the sailboat, the waves of the lake, and the forest after the sharpening process (Figures 10(c) and 10(d)). The results of the test image “Baboon” are shown in Figure 11. As can be seen in Figures 11(c) and 11(d), the contour around the eyes, and the beard or moustache of the baboon have become quite obvious when compared with the original image in Figure 11(a). Figure 12 shows the results of the test image “Foster City, CA”, an aerial image. A remarkable contour around the buildings, the bridges, and the roads can be obtained after the proposed sharpening process (Figures 12(c) and 12(d)) when compared with that of in the original image (Figure 12(a)). For the test image “Tiffany”, we show in Figures 13(c) and 13(d) the sharpened results by using the proposed approach. As can be seen in Figures 13(c) and 13(d), a very distinct contour around her eyes and around her fingers can be obtained after the sharpening process when compared with that of the original image in Figure 13(a).


An efficient and self-adapted approach to the sharpening of color images.

Kau LJ, Lee TL - ScientificWorldJournal (2013)

θeth = 22 for HVD. (a) The image “Peppers” (512 × 512 color image). (b) Edges detected by HVD with LPF. (c and d) Sharpened results by HVD with scaling factors 0.5 and 1.0, respectively.
© Copyright Policy - open-access
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3852310&req=5

fig7: θeth = 22 for HVD. (a) The image “Peppers” (512 × 512 color image). (b) Edges detected by HVD with LPF. (c and d) Sharpened results by HVD with scaling factors 0.5 and 1.0, respectively.
Mentions: In addition, we also show from Figures 6to 13 the sharpened results obtained by using the proposed approach to eight other color test images. As can be seen in Figures 6(c) and 6(d), the contour of the plane, the text on the plane, the pilot, and the mountain all have a very good visual quality when compared with the original image in Figure 6(a). For the test image “Peppers” in Figure 7, we can see in Figures 7(c) and 7(d) a very distinct contour around peppers and around the stalk of these peppers after the sharpening process when compared with the original image in Figure 7(a). For the test image “Woodland Hills, CA”, an aerial image, in Figure 8, we can see that the contour of the mountain, lake, roads and buildings are quite distinct in Figures 8(c) and 8(d) after the proposed sharpening process. Figure 9 shows the results of the well-known test image “Lena”. As can be seen in Figures 9(c) and 9(d), the contour around her eyes and the contour of the hair have become very conspicuous after the sharpening process. Figure 10 shows the results of the test image “Sailboat on lake”. When compared with the original image in Figure 10(a), a more conspicuous contour can be obtained for the sailboat, the waves of the lake, and the forest after the sharpening process (Figures 10(c) and 10(d)). The results of the test image “Baboon” are shown in Figure 11. As can be seen in Figures 11(c) and 11(d), the contour around the eyes, and the beard or moustache of the baboon have become quite obvious when compared with the original image in Figure 11(a). Figure 12 shows the results of the test image “Foster City, CA”, an aerial image. A remarkable contour around the buildings, the bridges, and the roads can be obtained after the proposed sharpening process (Figures 12(c) and 12(d)) when compared with that of in the original image (Figure 12(a)). For the test image “Tiffany”, we show in Figures 13(c) and 13(d) the sharpened results by using the proposed approach. As can be seen in Figures 13(c) and 13(d), a very distinct contour around her eyes and around her fingers can be obtained after the sharpening process when compared with that of the original image in Figure 13(a).

Bottom Line: With the proposed approach, the discontinuities can be highlighted while most of the original information contained in the image can be retained.Finally, the adjusted channel of Value and that of Hue and Saturation will be integrated to get the sharpened color image.Extensive experiments on natural images will be given in this paper to highlight the effectiveness and efficiency of the proposed approach.

View Article: PubMed Central - PubMed

Affiliation: Department of Electronic Engineering & Graduate Institute of Computer and Communication Engineering, National Taipei University of Technology, No. 1 Section 3, Chung-Hsiao E. Road, Taipei 10608, Taiwan.

ABSTRACT
An efficient approach to the sharpening of color images is proposed in this paper. For this, the image to be sharpened is first transformed to the HSV color model, and then only the channel of Value will be used for the process of sharpening while the other channels are left unchanged. We then apply a proposed edge detector and low-pass filter to the channel of Value to pick out pixels around boundaries. After that, those pixels detected as around edges or boundaries are adjusted so that the boundary can be sharpened, and those nonedge pixels are kept unaltered. The increment or decrement magnitude that is to be added to those edge pixels is determined in an adaptive manner based on global statistics of the image and local statistics of the pixel to be sharpened. With the proposed approach, the discontinuities can be highlighted while most of the original information contained in the image can be retained. Finally, the adjusted channel of Value and that of Hue and Saturation will be integrated to get the sharpened color image. Extensive experiments on natural images will be given in this paper to highlight the effectiveness and efficiency of the proposed approach.

Show MeSH
Related in: MedlinePlus